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Sample records for proposed method based

  1. Proposal for Requirement Validation Criteria and Method Based on Actor Interaction

    Science.gov (United States)

    Hattori, Noboru; Yamamoto, Shuichiro; Ajisaka, Tsuneo; Kitani, Tsuyoshi

    We propose requirement validation criteria and a method based on the interaction between actors in an information system. We focus on the cyclical transitions of one actor's situation against another and clarify observable stimuli and responses based on these transitions. Both actors' situations can be listed in a state transition table, which describes the observable stimuli or responses they send or receive. Examination of the interaction between both actors in the state transition tables enables us to detect missing or defective observable stimuli or responses. Typically, this method can be applied to the examination of the interaction between a resource managed by the information system and its user. As a case study, we analyzed 332 requirement defect reports of an actual system development project in Japan. We found that there were a certain amount of defects regarding missing or defective stimuli and responses, which can be detected using our proposed method if this method is used in the requirement definition phase. This means that we can reach a more complete requirement definition with our proposed method.

  2. Proposed Sandia frequency shift for anti-islanding detection method based on artificial immune system

    Directory of Open Access Journals (Sweden)

    A.Y. Hatata

    2018-03-01

    Full Text Available Sandia frequency shift (SFS is one of the active anti-islanding detection methods that depend on frequency drift to detect an islanding condition for inverter-based distributed generation. The non-detection zone (NDZ of the SFS method depends to a great extent on its parameters. Improper adjusting of these parameters may result in failure of the method. This paper presents a proposed artificial immune system (AIS-based technique to obtain optimal parameters of SFS anti-islanding detection method. The immune system is highly distributed, highly adaptive, and self-organizing in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. The proposed method generates less total harmonic distortion (THD than the conventional SFS, which results in faster island detection and better non-detection zone. The performance of the proposed method is derived analytically and simulated using Matlab/Simulink. Two case studies are used to verify the proposed method. The first case includes a photovoltaic (PV connected to grid and the second includes a wind turbine connected to grid. The deduced optimized parameter setting helps to achieve the “non-islanding inverter” as well as least potential adverse impact on power quality. Keywords: Anti-islanding detection, Sandia frequency shift (SFS, Non-detection zone (NDZ, Total harmonic distortion (THD, Artificial immune system (AIS, Clonal selection algorithm

  3. A Proposal on the Advanced Sampling Based Sensitivity and Uncertainty Analysis Method for the Eigenvalue Uncertainty Analysis

    International Nuclear Information System (INIS)

    Kim, Song Hyun; Song, Myung Sub; Shin, Chang Ho; Noh, Jae Man

    2014-01-01

    In using the perturbation theory, the uncertainty of the response can be estimated by a single transport simulation, and therefore it requires small computational load. However, it has a disadvantage that the computation methodology must be modified whenever estimating different response type such as multiplication factor, flux, or power distribution. Hence, it is suitable for analyzing few responses with lots of perturbed parameters. Statistical approach is a sampling based method which uses randomly sampled cross sections from covariance data for analyzing the uncertainty of the response. XSUSA is a code based on the statistical approach. The cross sections are only modified with the sampling based method; thus, general transport codes can be directly utilized for the S/U analysis without any code modifications. However, to calculate the uncertainty distribution from the result, code simulation should be enough repeated with randomly sampled cross sections. Therefore, this inefficiency is known as a disadvantage of the stochastic method. In this study, an advanced sampling method of the cross sections is proposed and verified to increase the estimation efficiency of the sampling based method. In this study, to increase the estimation efficiency of the sampling based S/U method, an advanced sampling and estimation method was proposed. The main feature of the proposed method is that the cross section averaged from each single sampled cross section is used. For the use of the proposed method, the validation was performed using the perturbation theory

  4. A Proposal of Estimation Methodology to Improve Calculation Efficiency of Sampling-based Method in Nuclear Data Sensitivity and Uncertainty Analysis

    International Nuclear Information System (INIS)

    Song, Myung Sub; Kim, Song Hyun; Kim, Jong Kyung; Noh, Jae Man

    2014-01-01

    The uncertainty with the sampling-based method is evaluated by repeating transport calculations with a number of cross section data sampled from the covariance uncertainty data. In the transport calculation with the sampling-based method, the transport equation is not modified; therefore, all uncertainties of the responses such as k eff , reaction rates, flux and power distribution can be directly obtained all at one time without code modification. However, a major drawback with the sampling-based method is that it requires expensive computational load for statistically reliable results (inside confidence level 0.95) in the uncertainty analysis. The purpose of this study is to develop a method for improving the computational efficiency and obtaining highly reliable uncertainty result in using the sampling-based method with Monte Carlo simulation. The proposed method is a method to reduce the convergence time of the response uncertainty by using the multiple sets of sampled group cross sections in a single Monte Carlo simulation. The proposed method was verified by estimating GODIVA benchmark problem and the results were compared with that of conventional sampling-based method. In this study, sampling-based method based on central limit theorem is proposed to improve calculation efficiency by reducing the number of repetitive Monte Carlo transport calculation required to obtain reliable uncertainty analysis results. Each set of sampled group cross sections is assigned to each active cycle group in a single Monte Carlo simulation. The criticality uncertainty for the GODIVA problem is evaluated by the proposed and previous method. The results show that the proposed sampling-based method can efficiently decrease the number of Monte Carlo simulation required for evaluate uncertainty of k eff . It is expected that the proposed method will improve computational efficiency of uncertainty analysis with sampling-based method

  5. Comments and Remarks over Classic Linear Loop-Gain Method for Oscillator Design and Analysis. New Proposed Method Based on NDF/RRT

    Directory of Open Access Journals (Sweden)

    J. L. Jimenez-Martin

    2012-04-01

    Full Text Available Present paper describes a new method for designing oscillators based on the Normalized Determinant Function (NDF and Return Relations (RRT . First a review of the loop-gain method will be performed, showing pros, cons and including some examples for exploring wrong so- lutions provided by this method. Wrong solutions, because some conditions have to be previously fulfilled in order to obtain right ones, which will be described and finally, demonstrate that NDF analysis is necessary, including Return Relations (RRT usefulness, which in fact are related with the True Loop-Gain. Finally concluding this paper, steps for oscillator design and analysis, using the proposed NDF/RRT method will be presented, compared to wrong previous solutions pointing out new accuracy achieved on oscillation frequency and QL prediction. Also, more new examples, of plane reference oscillators (Z/Y/rho, will be added for which loop gain method application is clearly difficult or even impossible, solving them with the new proposed NDF/RRT method.

  6. Evaluation of a proposed optimization method for discrete-event simulation models

    Directory of Open Access Journals (Sweden)

    Alexandre Ferreira de Pinho

    2012-12-01

    Full Text Available Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.

  7. A method proposal for cumulative environmental impact assessment based on the landscape vulnerability evaluation

    International Nuclear Information System (INIS)

    Pavlickova, Katarina; Vyskupova, Monika

    2015-01-01

    Cumulative environmental impact assessment deals with the occasional use in practical application of environmental impact assessment process. The main reasons are the difficulty of cumulative impact identification caused by lack of data, inability to measure the intensity and spatial effect of all types of impacts and the uncertainty of their future evolution. This work presents a method proposal to predict cumulative impacts on the basis of landscape vulnerability evaluation. For this purpose, qualitative assessment of landscape ecological stability is conducted and major vulnerability indicators of environmental and socio-economic receptors are specified and valuated. Potential cumulative impacts and the overall impact significance are predicted quantitatively in modified Argonne multiple matrixes while considering the vulnerability of affected landscape receptors and the significance of impacts identified individually. The method was employed in the concrete environmental impact assessment process conducted in Slovakia. The results obtained in this case study reflect that this methodology is simple to apply, valid for all types of impacts and projects, inexpensive and not time-consuming. The objectivity of the partial methods used in this procedure is improved by quantitative landscape ecological stability evaluation, assignment of weights to vulnerability indicators based on the detailed characteristics of affected factors, and grading impact significance. - Highlights: • This paper suggests a method proposal for cumulative impact prediction. • The method includes landscape vulnerability evaluation. • The vulnerability of affected receptors is determined by their sensitivity. • This method can increase the objectivity of impact prediction in the EIA process

  8. Determination of the oxidizing property: proposal of an alternative method based on differential scanning calorimetry

    International Nuclear Information System (INIS)

    Gigante, L.; Dellavedova, M.; Pasturenzi, C.; Lunghi, A.; Mattarella, M.; Cardillo, P.

    2008-01-01

    Determination of chemical-physical and hazardous properties of substances is a very important matter in the chemical industry, considering the growing attention of public opinion regarding safety and eco-compatibility aspects of products. In the present work, attention was focused on characterization of oxidizing properties. In case of solid compounds, the current method (Dir 84/449/CEE 6) compares the maximum combustion rate of the examined substance to the maximum combustion rate of a reference mixture. This method shows a lot of disvantages and does not provide a quantitative result. In the following work an alternative method, based on DSC measurements, is proposed for the determination of oxidizing properties. [it

  9. Proposal of Constraints Analysis Method Based on Network Model for Task Planning

    Science.gov (United States)

    Tomiyama, Tomoe; Sato, Tatsuhiro; Morita, Toyohisa; Sasaki, Toshiro

    Deregulation has been accelerating several activities toward reengineering business processes, such as railway through service and modal shift in logistics. Making those activities successful, business entities have to regulate new business rules or know-how (we call them ‘constraints’). According to the new constraints, they need to manage business resources such as instruments, materials, workers and so on. In this paper, we propose a constraint analysis method to define constraints for task planning of the new business processes. To visualize each constraint's influence on planning, we propose a network model which represents allocation relations between tasks and resources. The network can also represent task ordering relations and resource grouping relations. The proposed method formalizes the way of defining constraints manually as repeatedly checking the network structure and finding conflicts between constraints. Being applied to crew scheduling problems shows that the method can adequately represent and define constraints of some task planning problems with the following fundamental features, (1) specifying work pattern to some resources, (2) restricting the number of resources for some works, (3) requiring multiple resources for some works, (4) prior allocation of some resources to some works and (5) considering the workload balance between resources.

  10. A Proposed Method for Solving Fuzzy System of Linear Equations

    Directory of Open Access Journals (Sweden)

    Reza Kargar

    2014-01-01

    Full Text Available This paper proposes a new method for solving fuzzy system of linear equations with crisp coefficients matrix and fuzzy or interval right hand side. Some conditions for the existence of a fuzzy or interval solution of m×n linear system are derived and also a practical algorithm is introduced in detail. The method is based on linear programming problem. Finally the applicability of the proposed method is illustrated by some numerical examples.

  11. A proposal on alternative sampling-based modeling method of spherical particles in stochastic media for Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Lee, Jae Yong; KIm, Do Hyun; Kim, Jong Kyung [Dept. of Nuclear Engineering, Hanyang University, Seoul (Korea, Republic of); Noh, Jae Man [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-08-15

    Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

  12. A proposal on alternative sampling-based modeling method of spherical particles in stochastic media for Monte Carlo simulation

    International Nuclear Information System (INIS)

    Kim, Song Hyun; Lee, Jae Yong; KIm, Do Hyun; Kim, Jong Kyung; Noh, Jae Man

    2015-01-01

    Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media

  13. Small Private Online Research: A Proposal for A Numerical Methods Course Based on Technology Use and Blended Learning

    Science.gov (United States)

    Cepeda, Francisco Javier Delgado

    2017-01-01

    This work presents a proposed model in blended learning for a numerical methods course evolved from traditional teaching into a research lab in scientific visualization. The blended learning approach sets a differentiated and flexible scheme based on a mobile setup and face to face sessions centered on a net of research challenges. Model is…

  14. Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

    Directory of Open Access Journals (Sweden)

    Navid Hooshangi

    2018-01-01

    Full Text Available Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR operations. The present study aimed to develop a dynamic agent-based simulation model in post-earthquake USAR operations using geospatial information system and multi agent systems (GIS and MASs, respectively. We also propose an approach for dynamic task allocation and establishing collaboration among agents based on contract net protocol (CNP and interval-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS methods, which consider uncertainty in natural hazards information during agents’ decision-making. The decision-making weights were calculated by analytic hierarchy process (AHP. In order to implement the system, earthquake environment was simulated and the damage of the buildings and a number of injuries were calculated in Tehran’s District 3: 23%, 37%, 24% and 16% of buildings were in slight, moderate, extensive and completely vulnerable classes, respectively. The number of injured persons was calculated to be 17,238. Numerical results in 27 scenarios showed that the proposed method is more accurate than the CNP method in the terms of USAR operational time (at least 13% decrease and the number of human fatalities (at least 9% decrease. In interval uncertainty analysis of our proposed simulated system, the lower and upper bounds of uncertain responses are evaluated. The overall results showed that considering uncertainty in task allocation can be a highly advantageous in the disaster environment. Such systems can be used to manage and prepare for natural hazards.

  15. Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

    Directory of Open Access Journals (Sweden)

    Anh Vu Le

    2017-01-01

    Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

  16. Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone

    Directory of Open Access Journals (Sweden)

    Rifat Zaman

    2017-02-01

    Full Text Available We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

  17. A Proposal of New Spherical Particle Modeling Method Based on Stochastic Sampling of Particle Locations in Monte Carlo Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Kim, Do Hyun; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of); Noh, Jea Man [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    To the high computational efficiency and user convenience, the implicit method had received attention; however, it is noted that the implicit method in the previous studies has low accuracy at high packing fraction. In this study, a new implicit method, which can be used at any packing fraction with high accuracy, is proposed. In this study, the implicit modeling method in the spherical particle distributed medium for using the MC simulation is proposed. A new concept in the spherical particle sampling was developed to solve the problems in the previous implicit methods. The sampling method was verified by simulating the sampling method in the infinite and finite medium. The results show that the particle implicit modeling with the proposed method was accurately performed in all packing fraction boundaries. It is expected that the proposed method can be efficiently utilized for the spherical particle distributed mediums, which are the fusion reactor blanket, VHTR reactors, and shielding analysis.

  18. Applicability of the proposed evaluation method for social infrastructures to nuclear power plants

    International Nuclear Information System (INIS)

    Ichimura, Tomiyasu

    2015-01-01

    This study proposes an evaluation method for social infrastructures, and verifies the applicability of the proposed evaluation method to social infrastructures by applying it to nuclear power plants, which belong to social infrastructures. In the proposed evaluation method for social infrastructures, the authors chose four evaluation viewpoints and proposed common evaluation standards for the evaluation indexes obtained from each viewpoint. By applying this system to the evaluation of nuclear power plants, the evaluation index examples were obtained from the evaluation viewpoints. Furthermore, when the level of the common evaluation standards of the proposed evaluation method was applied to the evaluation of the activities of nuclear power plants based on the regulations, it was confirmed that these activities are at the highest level. Through this application validation, it was clarified that the proposed evaluation method for social infrastructures had certain effectiveness. The four evaluation viewpoints are 'service,' 'environment,' 'action factor,' and 'operation and management.' Part of the application examples to a nuclear power plant are as follows: (1) in the viewpoint of service: the operation rate of the power plant, and operation costs, and (2) in the viewpoint of environment: external influence related to nuclear waste and radioactivity, and external effect related to cooling water. (A.O.)

  19. A Channelization-Based DOA Estimation Method for Wideband Signals

    Directory of Open Access Journals (Sweden)

    Rui Guo

    2016-07-01

    Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

  20. Proposal of a method for evaluating tsunami risk using response-surface methodology

    Science.gov (United States)

    Fukutani, Y.

    2017-12-01

    Information on probabilistic tsunami inundation hazards is needed to define and evaluate tsunami risk. Several methods for calculating these hazards have been proposed (e.g. Løvholt et al. (2012), Thio (2012), Fukutani et al. (2014), Goda et al. (2015)). However, these methods are inefficient, and their calculation cost is high, since they require multiple tsunami numerical simulations, therefore lacking versatility. In this study, we proposed a simpler method for tsunami risk evaluation using response-surface methodology. Kotani et al. (2016) proposed an evaluation method for the probabilistic distribution of tsunami wave-height using a response-surface methodology. We expanded their study and developed a probabilistic distribution of tsunami inundation depth. We set the depth (x1) and the slip (x2) of an earthquake fault as explanatory variables and tsunami inundation depth (y) as an object variable. Subsequently, tsunami risk could be evaluated by conducting a Monte Carlo simulation, assuming that the generation probability of an earthquake follows a Poisson distribution, the probability distribution of tsunami inundation depth follows the distribution derived from a response-surface, and the damage probability of a target follows a log normal distribution. We applied the proposed method to a wood building located on the coast of Tokyo Bay. We implemented a regression analysis based on the results of 25 tsunami numerical calculations and developed a response-surface, which was defined as y=ax1+bx2+c (a:0.2615, b:3.1763, c=-1.1802). We assumed proper probabilistic distribution for earthquake generation, inundation height, and vulnerability. Based on these probabilistic distributions, we conducted Monte Carlo simulations of 1,000,000 years. We clarified that the expected damage probability of the studied wood building is 22.5%, assuming that an earthquake occurs. The proposed method is therefore a useful and simple way to evaluate tsunami risk using a response

  1. Validation of a method for assessing resident physicians' quality improvement proposals.

    Science.gov (United States)

    Leenstra, James L; Beckman, Thomas J; Reed, Darcy A; Mundell, William C; Thomas, Kris G; Krajicek, Bryan J; Cha, Stephen S; Kolars, Joseph C; McDonald, Furman S

    2007-09-01

    Residency programs involve trainees in quality improvement (QI) projects to evaluate competency in systems-based practice and practice-based learning and improvement. Valid approaches to assess QI proposals are lacking. We developed an instrument for assessing resident QI proposals--the Quality Improvement Proposal Assessment Tool (QIPAT-7)-and determined its validity and reliability. QIPAT-7 content was initially obtained from a national panel of QI experts. Through an iterative process, the instrument was refined, pilot-tested, and revised. Seven raters used the instrument to assess 45 resident QI proposals. Principal factor analysis was used to explore the dimensionality of instrument scores. Cronbach's alpha and intraclass correlations were calculated to determine internal consistency and interrater reliability, respectively. QIPAT-7 items comprised a single factor (eigenvalue = 3.4) suggesting a single assessment dimension. Interrater reliability for each item (range 0.79 to 0.93) and internal consistency reliability among the items (Cronbach's alpha = 0.87) were high. This method for assessing resident physician QI proposals is supported by content and internal structure validity evidence. QIPAT-7 is a useful tool for assessing resident QI proposals. Future research should determine the reliability of QIPAT-7 scores in other residency and fellowship training programs. Correlations should also be made between assessment scores and criteria for QI proposal success such as implementation of QI proposals, resident scholarly productivity, and improved patient outcomes.

  2. Proposal of a New Method for Neutron Dosimetry Based on Spectral Information Obtained by Application of Artificial Neural Networks

    International Nuclear Information System (INIS)

    Fehrenbacher, G.; Schuetz, R.; Hahn, K.; Sprunck, M.; Cordes, E.; Biersack, J.P.; Wahl, W.

    1999-01-01

    A new method for the monitoring of neutron radiation is proposed. It is based on the determination of spectral information on the neutron field in order to derive dose quantities like the ambient dose equivalent, the dose equivalent, or other dose quantities which depend on the neutron energy. The method uses a multi-element system consisting of converter type silicon detectors. The unfolding procedure is based on an artificial neural network (ANN). The response function of each element is determined by a computational model considering the neutron interaction with the dosemeter layers and the subsequent transport of produced ions. An example is given for a multi-element system. The ANN is trained by a given set of neutron spectra and then applied to count responses obtained in neutron fields. Four examples of spectra unfolded using the ANN are presented. (author)

  3. A novel method of S-box design based on chaotic map and composition method

    International Nuclear Information System (INIS)

    Lambić, Dragan

    2014-01-01

    Highlights: • Novel chaotic S-box generation method is presented. • Presented S-box has better cryptographic properties than other examples of chaotic S-boxes. • The advantages of the proposed method are the low complexity and large key space. -- Abstract: An efficient algorithm for obtaining random bijective S-boxes based on chaotic maps and composition method is presented. The proposed method is based on compositions of S-boxes from a fixed starting set. The sequence of the indices of starting S-boxes used is obtained by using chaotic maps. The results of performance test show that the S-box presented in this paper has good cryptographic properties. The advantages of the proposed method are the low complexity and the possibility to achieve large key space

  4. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  5. Metamodel-based inverse method for parameter identification: elastic-plastic damage model

    Science.gov (United States)

    Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

    2017-04-01

    This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

  6. A Hybrid Positioning Method Based on Hypothesis Testing

    DEFF Research Database (Denmark)

    Amiot, Nicolas; Pedersen, Troels; Laaraiedh, Mohamed

    2012-01-01

    maxima. We propose to first estimate the support region of the two peaks of the likelihood function using a set membership method, and then decide between the two regions using a rule based on the less reliable observations. Monte Carlo simulations show that the performance of the proposed method...

  7. Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

    Science.gov (United States)

    Betta, G.; Capriglione, D.; Crenna, F.; Rossi, G. B.; Gasparetto, M.; Zappa, E.; Liguori, C.; Paolillo, A.

    2011-12-01

    Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection.

  8. Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

    International Nuclear Information System (INIS)

    Betta, G; Capriglione, D; Crenna, F; Rossi, G B; Gasparetto, M; Zappa, E; Liguori, C; Paolillo, A

    2011-01-01

    Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection

  9. Power quality events recognition using a SVM-based method

    Energy Technology Data Exchange (ETDEWEB)

    Cerqueira, Augusto Santiago; Ferreira, Danton Diego; Ribeiro, Moises Vidal; Duque, Carlos Augusto [Department of Electrical Circuits, Federal University of Juiz de Fora, Campus Universitario, 36036 900, Juiz de Fora MG (Brazil)

    2008-09-15

    In this paper, a novel SVM-based method for power quality event classification is proposed. A simple approach for feature extraction is introduced, based on the subtraction of the fundamental component from the acquired voltage signal. The resulting signal is presented to a support vector machine for event classification. Results from simulation are presented and compared with two other methods, the OTFR and the LCEC. The proposed method shown an improved performance followed by a reasonable computational cost. (author)

  10. Assessment of proposed electromagnetic quantum vacuum energy extraction methods

    OpenAIRE

    Moddel, Garret

    2009-01-01

    In research articles and patents several methods have been proposed for the extraction of zero-point energy from the vacuum. None has been reliably demonstrated, but the proposals remain largely unchallenged. In this paper the feasibility of these methods is assessed in terms of underlying thermodynamics principles of equilibrium, detailed balance, and conservation laws. The methods are separated into three classes: nonlinear processing of the zero-point field, mechanical extraction using Cas...

  11. Ontology-Based Method for Fault Diagnosis of Loaders.

    Science.gov (United States)

    Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

    2018-02-28

    This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

  12. Proposal of Evolutionary Simplex Method for Global Optimization Problem

    Science.gov (United States)

    Shimizu, Yoshiaki

    To make an agile decision in a rational manner, role of optimization engineering has been notified increasingly under diversified customer demand. With this point of view, in this paper, we have proposed a new evolutionary method serving as an optimization technique in the paradigm of optimization engineering. The developed method has prospects to solve globally various complicated problem appearing in real world applications. It is evolved from the conventional method known as Nelder and Mead’s Simplex method by virtue of idea borrowed from recent meta-heuristic method such as PSO. Mentioning an algorithm to handle linear inequality constraints effectively, we have validated effectiveness of the proposed method through comparison with other methods using several benchmark problems.

  13. Bus Based Synchronization Method for CHIPPER Based NoC

    Directory of Open Access Journals (Sweden)

    D. Muralidharan

    2016-01-01

    Full Text Available Network on Chip (NoC reduces the communication delay of System on Chip (SoC. The main limitation of NoC is power consumption and area overhead. Bufferless NoC reduces the area complexity and power consumption by eliminating buffers in the traditional routers. The bufferless NoC design should include live lock freeness since they use hot potato routing. This increases the complexity of bufferless NoC design. Among the available propositions to reduce this complexity, CHIPPER based bufferless NoC is considered as one of the best options. Live lock freeness is provided in CHIPPER through golden epoch and golden packet. All routers follow some synchronization method to identify a golden packet. Clock based method is intuitively followed for synchronization in CHIPPER based NoCs. It is shown in this work that the worst-case latency of packets is unbearably high when the above synchronization is followed. To alleviate this problem, broadcast bus NoC (BBus NoC approach is proposed in this work. The proposed method decreases the worst-case latency of packets by increasing the golden epoch rate of CHIPPER.

  14. Enhancements to Graph based methods for Multi Document Summarization

    Directory of Open Access Journals (Sweden)

    Rengaramanujam Srinivasan

    2009-01-01

    Full Text Available This paper focuses its attention on extractivesummarization using popular graph based approaches. Graphbased methods can be broadly classified into two categories:non- PageRank type and PageRank type methods. Of themethods already proposed - the Centrality Degree methodbelongs to the former category while LexRank and ContinuousLexRank methods belong to later category. The paper goes on tosuggest two enhancements to both PageRank type and non-PageRank type methods. The first modification is that ofrecursively discounting the selected sentences, i.e. if a sentence isselected it is removed from further consideration and the nextsentence is selected based upon the contributions of theremaining sentences only. Next the paper suggests a method ofincorporating position weight to these schemes. In all 14methods –six of non- PageRank type and eight of PageRanktype have been investigated. To clearly distinguish betweenvarious schemes, we call the methods of incorporatingdiscounting and position weight enhancements over LexicalRank schemes as Sentence Rank (SR methods. Intrinsicevaluation of all the 14 graph based methods were done usingconventional Precision metric and metrics earlier proposed byus - Effectiveness1 (E1 and Effectiveness2 (E2. Experimentalstudy brings out that the proposed SR methods are superior toall the other methods.

  15. New component-based normalization method to correct PET system models

    International Nuclear Information System (INIS)

    Kinouchi, Shoko; Miyoshi, Yuji; Suga, Mikio; Yamaya, Taiga; Yoshida, Eiji; Nishikido, Fumihiko; Tashima, Hideaki

    2011-01-01

    Normalization correction is necessary to obtain high-quality reconstructed images in positron emission tomography (PET). There are two basic types of normalization methods: the direct method and component-based methods. The former method suffers from the problem that a huge count number in the blank scan data is required. Therefore, the latter methods have been proposed to obtain high statistical accuracy normalization coefficients with a small count number in the blank scan data. In iterative image reconstruction methods, on the other hand, the quality of the obtained reconstructed images depends on the system modeling accuracy. Therefore, the normalization weighing approach, in which normalization coefficients are directly applied to the system matrix instead of a sinogram, has been proposed. In this paper, we propose a new component-based normalization method to correct system model accuracy. In the proposed method, two components are defined and are calculated iteratively in such a way as to minimize errors of system modeling. To compare the proposed method and the direct method, we applied both methods to our small OpenPET prototype system. We achieved acceptable statistical accuracy of normalization coefficients while reducing the count number of the blank scan data to one-fortieth that required in the direct method. (author)

  16. A Proposed Arabic Handwritten Text Normalization Method

    Directory of Open Access Journals (Sweden)

    Tarik Abu-Ain

    2014-11-01

    Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

  17. Phase Difference Measurement Method Based on Progressive Phase Shift

    Directory of Open Access Journals (Sweden)

    Min Zhang

    2018-06-01

    Full Text Available This paper proposes a method for phase difference measurement based on the principle of progressive phase shift (PPS. A phase difference measurement system based on PPS and implemented in the FPGA chip is proposed and tested. In the realized system, a fully programmable delay line (PDL is constructed, which provides accurate and stable delay, benefitting from the feed-back structure of the control module. The control module calibrates the delay according to process, voltage and temperature (PVT variations. Furthermore, a modified method based on double PPS is incorporated to improve the resolution. The obtained resolution is 25 ps. Moreover, to improve the resolution, the proposed method is implemented on the 20 nm Xilinx Kintex Ultrascale platform, and test results indicate that the obtained measurement error and clock synchronization error is within the range of ±5 ps.

  18. Proposal and Implementation of a Robust Sensing Method for DVB-T Signal

    Science.gov (United States)

    Song, Chunyi; Rahman, Mohammad Azizur; Harada, Hiroshi

    This paper proposes a sensing method for TV signals of DVB-T standard to realize effective TV White Space (TVWS) Communication. In the TVWS technology trial organized by the Infocomm Development Authority (iDA) of Singapore, with regard to the sensing level and sensing time, detecting DVB-T signal at the level of -120dBm over an 8MHz channel with a sensing time below 1 second is required. To fulfill such a strict sensing requirement, we propose a smart sensing method which combines feature detection and energy detection (CFED), and is also characterized by using dynamic threshold selection (DTS) based on a threshold table to improve sensing robustness to noise uncertainty. The DTS based CFED (DTS-CFED) is evaluated by computer simulations and is also implemented into a hardware sensing prototype. The results show that the DTS-CFED achieves a detection probability above 0.9 for a target false alarm probability of 0.1 for DVB-T signals at the level of -120dBm over an 8MHz channel with the sensing time equals to 0.1 second.

  19. A proposed HTTP service based IDS

    Directory of Open Access Journals (Sweden)

    Mohamed M. Abd-Eldayem

    2014-03-01

    Full Text Available The tremendous growth of the web-based applications has increased information security vulnerabilities over the Internet. Security administrators use Intrusion-Detection System (IDS to monitor network traffic and host activities to detect attacks against hosts and network resources. In this paper IDS based on Naïve Bayes classifier is analyzed. The main objective is to enhance IDS performance through preparing the training data set allowing to detect malicious connections that exploit the http service. Results of application are demonstrated and discussed. In the training phase of the proposed IDS, at first a feature selection technique based on Naïve Bayes classifier is used, this technique identifies the most important HTTP traffic features that can be used to detect HTTP attacks. In the testing and running phases proposed IDS classifies the network traffic based on the requested service, then based on the selected features Naïve Bayes classifier is used to analyze the HTTP service based traffic and identifies the HTTP normal connections and attacks. The performance of the IDS is measured through experiments using NSL-KDD data set. The results show that the detection rate of the IDS is about 99%, the false-positive rate is about 1%, and the false-negative rate is about 0.25%; therefore, proposed IDS holds the highest detection rate and the lowest false alarm compared with other leading IDS. In addition, the proposed IDS based on Naïve Bayes is used to classify network connections as a normal or attack. And it holds a high detection rate and a low false alarm.

  20. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    Directory of Open Access Journals (Sweden)

    Sadegh Aminifar

    2013-01-01

    Full Text Available Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal and vertical rule bases method has a great roll in easing of extracting the optimum control surface by using too lesser rules than traditional fuzzy systems. This research involves with control of a system with high nonlinearity and in difficulty to model it with classical methods. As a case study for testing proposed method in real condition, the designed controller is applied to steaming room with uncertain data and variable parameters. A comparison between PID and traditional fuzzy counterpart and our proposed system shows that our proposed system outperforms PID and traditional fuzzy systems in point of view of number of valve switching and better surface following. The evaluations have done both with model simulation and DSP implementation.

  1. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  2. Therapy Decision Support Based on Recommender System Methods.

    Science.gov (United States)

    Gräßer, Felix; Beckert, Stefanie; Küster, Denise; Schmitt, Jochen; Abraham, Susanne; Malberg, Hagen; Zaunseder, Sebastian

    2017-01-01

    We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender , are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  3. Content-based quality evaluation of color images: overview and proposals

    Science.gov (United States)

    Tremeau, Alain; Richard, Noel; Colantoni, Philippe; Fernandez-Maloigne, Christine

    2003-12-01

    The automatic prediction of perceived quality from image data in general, and the assessment of particular image characteristics or attributes that may need improvement in particular, becomes an increasingly important part of intelligent imaging systems. The purpose of this paper is to propose to the color imaging community in general to develop a software package available on internet to help the user to select among all these approaches which is better appropriated to a given application. The ultimate goal of this project is to propose, next to implement, an open and unified color imaging system to set up a favourable context for the evaluation and analysis of color imaging processes. Many different methods for measuring the performance of a process have been proposed by different researchers. In this paper, we will discuss the advantages and shortcomings of most of main analysis criteria and performance measures currently used. The aim is not to establish a harsh competition between algorithms or processes, but rather to test and compare the efficiency of methodologies firstly to highlight strengths and weaknesses of a given algorithm or methodology on a given image type and secondly to have these results publicly available. This paper is focused on two important unsolved problems. Why it is so difficult to select a color space which gives better results than another one? Why it is so difficult to select an image quality metric which gives better results than another one, with respect to the judgment of the Human Visual System? Several methods used either in color imaging or in image quality will be thus discussed. Proposals for content-based image measures and means of developing a standard test suite for will be then presented. The above reference advocates for an evaluation protocol based on an automated procedure. This is the ultimate goal of our proposal.

  4. Cryptanalysis of "an improvement over an image encryption method based on total shuffling"

    Science.gov (United States)

    Akhavan, A.; Samsudin, A.; Akhshani, A.

    2015-09-01

    In the past two decades, several image encryption algorithms based on chaotic systems had been proposed. Many of the proposed algorithms are meant to improve other chaos based and conventional cryptographic algorithms. Whereas, many of the proposed improvement methods suffer from serious security problems. In this paper, the security of the recently proposed improvement method for a chaos-based image encryption algorithm is analyzed. The results indicate the weakness of the analyzed algorithm against chosen plain-text.

  5. Comparison of model reference and map based control method for vehicle stability enhancement

    NARCIS (Netherlands)

    Baek, S.; Son, M.; Song, J.; Boo, K.; Kim, H.

    2012-01-01

    A map based controller method to improve a vehicle lateral stability is proposed in this study and compared with the conventional method, a model referenced controller. A model referenced controller to determine compensated yaw moment uses the sliding mode method, but the proposed map based

  6. Creep-fatigue evaluation method for weld joint of Mod.9Cr-1Mo steel Part II: Plate bending test and proposal of a simplified evaluation method

    Energy Technology Data Exchange (ETDEWEB)

    Ando, Masanori, E-mail: ando.masanori@jaea.go.jp; Takaya, Shigeru, E-mail: takaya.shigeru@jaea.go.jp

    2016-12-15

    Highlights: • Creep-fatigue evaluation method for weld joint of Mod.9Cr-1Mo steel is proposed. • A simplified evaluation method is also proposed for the codification. • Both proposed evaluation method was validated by the plate bending test. • For codification, the local stress and strain behavior was analyzed. - Abstract: In the present study, to develop an evaluation procedure and design rules for Mod.9Cr-1Mo steel weld joints, a method for evaluating the creep-fatigue life of Mod.9Cr-1Mo steel weld joints was proposed based on finite element analysis (FEA) and a series of cyclic plate bending tests of longitudinal and horizontal seamed plates. The strain concentration and redistribution behaviors were evaluated and the failure cycles were estimated using FEA by considering the test conditions and metallurgical discontinuities in the weld joints. Inelastic FEA models consisting of the base metal, heat-affected zone and weld metal were employed to estimate the elastic follow-up behavior caused by the metallurgical discontinuities. The elastic follow-up factors determined by comparing the elastic and inelastic FEA results were determined to be less than 1.5. Based on the estimated elastic follow-up factors obtained via inelastic FEA, a simplified technique using elastic FEA was proposed for evaluating the creep-fatigue life in Mod.9Cr-1Mo steel weld joints. The creep-fatigue life obtained using the plate bending test was compared to those estimated from the results of inelastic FEA and by a simplified evaluation method.

  7. Creep-fatigue evaluation method for weld joint of Mod.9Cr-1Mo steel Part II: Plate bending test and proposal of a simplified evaluation method

    International Nuclear Information System (INIS)

    Ando, Masanori; Takaya, Shigeru

    2016-01-01

    Highlights: • Creep-fatigue evaluation method for weld joint of Mod.9Cr-1Mo steel is proposed. • A simplified evaluation method is also proposed for the codification. • Both proposed evaluation method was validated by the plate bending test. • For codification, the local stress and strain behavior was analyzed. - Abstract: In the present study, to develop an evaluation procedure and design rules for Mod.9Cr-1Mo steel weld joints, a method for evaluating the creep-fatigue life of Mod.9Cr-1Mo steel weld joints was proposed based on finite element analysis (FEA) and a series of cyclic plate bending tests of longitudinal and horizontal seamed plates. The strain concentration and redistribution behaviors were evaluated and the failure cycles were estimated using FEA by considering the test conditions and metallurgical discontinuities in the weld joints. Inelastic FEA models consisting of the base metal, heat-affected zone and weld metal were employed to estimate the elastic follow-up behavior caused by the metallurgical discontinuities. The elastic follow-up factors determined by comparing the elastic and inelastic FEA results were determined to be less than 1.5. Based on the estimated elastic follow-up factors obtained via inelastic FEA, a simplified technique using elastic FEA was proposed for evaluating the creep-fatigue life in Mod.9Cr-1Mo steel weld joints. The creep-fatigue life obtained using the plate bending test was compared to those estimated from the results of inelastic FEA and by a simplified evaluation method.

  8. [A retrieval method of drug molecules based on graph collapsing].

    Science.gov (United States)

    Qu, J W; Lv, X Q; Liu, Z M; Liao, Y; Sun, P H; Wang, B; Tang, Z

    2018-04-18

    To establish a compact and efficient hypergraph representation and a graph-similarity-based retrieval method of molecules to achieve effective and efficient medicine information retrieval. Chemical structural formula (CSF) was a primary search target as a unique and precise identifier for each compound at the molecular level in the research field of medicine information retrieval. To retrieve medicine information effectively and efficiently, a complete workflow of the graph-based CSF retrieval system was introduced. This system accepted the photos taken from smartphones and the sketches drawn on tablet personal computers as CSF inputs, and formalized the CSFs with the corresponding graphs. Then this paper proposed a compact and efficient hypergraph representation for molecules on the basis of analyzing factors that directly affected the efficiency of graph matching. According to the characteristics of CSFs, a hierarchical collapsing method combining graph isomorphism and frequent subgraph mining was adopted. There was yet a fundamental challenge, subgraph overlapping during the collapsing procedure, which hindered the method from establishing the correct compact hypergraph of an original CSF graph. Therefore, a graph-isomorphism-based algorithm was proposed to select dominant acyclic subgraphs on the basis of overlapping analysis. Finally, the spatial similarity among graphical CSFs was evaluated by multi-dimensional measures of similarity. To evaluate the performance of the proposed method, the proposed system was firstly compared with Wikipedia Chemical Structure Explorer (WCSE), the state-of-the-art system that allowed CSF similarity searching within Wikipedia molecules dataset, on retrieval accuracy. The system achieved higher values on mean average precision, discounted cumulative gain, rank-biased precision, and expected reciprocal rank than WCSE from the top-2 to the top-10 retrieved results. Specifically, the system achieved 10%, 1.41, 6.42%, and 1

  9. Topology Optimization of Passive Micromixers Based on Lagrangian Mapping Method

    Directory of Open Access Journals (Sweden)

    Yuchen Guo

    2018-03-01

    Full Text Available This paper presents an optimization-based design method of passive micromixers for immiscible fluids, which means that the Peclet number infinitely large. Based on topology optimization method, an optimization model is constructed to find the optimal layout of the passive micromixers. Being different from the topology optimization methods with Eulerian description of the convection-diffusion dynamics, this proposed method considers the extreme case, where the mixing is dominated completely by the convection with negligible diffusion. In this method, the mixing dynamics is modeled by the mapping method, a Lagrangian description that can deal with the case with convection-dominance. Several numerical examples have been presented to demonstrate the validity of the proposed method.

  10. Reliability-based design optimization via high order response surface method

    International Nuclear Information System (INIS)

    Li, Hong Shuang

    2013-01-01

    To reduce the computational effort of reliability-based design optimization (RBDO), the response surface method (RSM) has been widely used to evaluate reliability constraints. We propose an efficient methodology for solving RBDO problems based on an improved high order response surface method (HORSM) that takes advantage of an efficient sampling method, Hermite polynomials and uncertainty contribution concept to construct a high order response surface function with cross terms for reliability analysis. The sampling method generates supporting points from Gauss-Hermite quadrature points, which can be used to approximate response surface function without cross terms, to identify the highest order of each random variable and to determine the significant variables connected with point estimate method. The cross terms between two significant random variables are added to the response surface function to improve the approximation accuracy. Integrating the nested strategy, the improved HORSM is explored in solving RBDO problems. Additionally, a sampling based reliability sensitivity analysis method is employed to reduce the computational effort further when design variables are distributional parameters of input random variables. The proposed methodology is applied on two test problems to validate its accuracy and efficiency. The proposed methodology is more efficient than first order reliability method based RBDO and Monte Carlo simulation based RBDO, and enables the use of RBDO as a practical design tool.

  11. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  12. Local coding based matching kernel method for image classification.

    Directory of Open Access Journals (Sweden)

    Yan Song

    Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

  13. Qualitative Assessment of Inquiry-Based Teaching Methods

    Science.gov (United States)

    Briggs, Michael; Long, George; Owens, Katrina

    2011-01-01

    A new approach to teaching method assessment using student focused qualitative studies and the theoretical framework of mental models is proposed. The methodology is considered specifically for the advantages it offers when applied to the assessment of inquiry-based teaching methods. The theoretical foundation of mental models is discussed, and…

  14. Multi person detection and tracking based on hierarchical level-set method

    Science.gov (United States)

    Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

    2018-04-01

    In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

  15. Therapy Decision Support Based on Recommender System Methods

    Directory of Open Access Journals (Sweden)

    Felix Gräßer

    2017-01-01

    Full Text Available We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  16. Qualitative Comparison of Contraction-Based Curve Skeletonization Methods

    NARCIS (Netherlands)

    Sobiecki, André; Yasan, Haluk C.; Jalba, Andrei C.; Telea, Alexandru C.

    2013-01-01

    In recent years, many new methods have been proposed for extracting curve skeletons of 3D shapes, using a mesh-contraction principle. However, it is still unclear how these methods perform with respect to each other, and with respect to earlier voxel-based skeletonization methods, from the viewpoint

  17. A Learning Method for Neural Networks Based on a Pseudoinverse Technique

    Directory of Open Access Journals (Sweden)

    Chinmoy Pal

    1996-01-01

    Full Text Available A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented. The efficiency and robustness of the method are verified with the help of an Exclusive OR problem and a dynamic system identification of a linear single degree of freedom mass–spring problem. It is observed that, compared with the conventional backpropagation method, the proposed method has a better convergence rate and a higher degree of learning accuracy with a lower equivalent learning coefficient. It is also found that unlike the steepest descent method, the learning capability of which is dependent on the value of the learning coefficient ν, the proposed pseudoinverse based backpropagation algorithm is comparatively robust with respect to its equivalent variable learning coefficient. A combination of the pseudoinverse method and the steepest descent method is proposed for a faster, more accurate learning capability.

  18. Correction of Misclassifications Using a Proximity-Based Estimation Method

    Directory of Open Access Journals (Sweden)

    Shmulevich Ilya

    2004-01-01

    Full Text Available An estimation method for correcting misclassifications in signal and image processing is presented. The method is based on the use of context-based (temporal or spatial information in a sliding-window fashion. The classes can be purely nominal, that is, an ordering of the classes is not required. The method employs nonlinear operations based on class proximities defined by a proximity matrix. Two case studies are presented. In the first, the proposed method is applied to one-dimensional signals for processing data that are obtained by a musical key-finding algorithm. In the second, the estimation method is applied to two-dimensional signals for correction of misclassifications in images. In the first case study, the proximity matrix employed by the estimation method follows directly from music perception studies, whereas in the second case study, the optimal proximity matrix is obtained with genetic algorithms as the learning rule in a training-based optimization framework. Simulation results are presented in both case studies and the degree of improvement in classification accuracy that is obtained by the proposed method is assessed statistically using Kappa analysis.

  19. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

    Directory of Open Access Journals (Sweden)

    Yonghao Gu

    2017-01-01

    Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

  20. Gene set analysis: limitations in popular existing methods and proposed improvements.

    Science.gov (United States)

    Mishra, Pashupati; Törönen, Petri; Leino, Yrjö; Holm, Liisa

    2014-10-01

    Gene set analysis is the analysis of a set of genes that collectively contribute to a biological process. Most popular gene set analysis methods are based on empirical P-value that requires large number of permutations. Despite numerous gene set analysis methods developed in the past decade, the most popular methods still suffer from serious limitations. We present a gene set analysis method (mGSZ) based on Gene Set Z-scoring function (GSZ) and asymptotic P-values. Asymptotic P-value calculation requires fewer permutations, and thus speeds up the gene set analysis process. We compare the GSZ-scoring function with seven popular gene set scoring functions and show that GSZ stands out as the best scoring function. In addition, we show improved performance of the GSA method when the max-mean statistics is replaced by the GSZ scoring function. We demonstrate the importance of both gene and sample permutations by showing the consequences in the absence of one or the other. A comparison of asymptotic and empirical methods of P-value estimation demonstrates a clear advantage of asymptotic P-value over empirical P-value. We show that mGSZ outperforms the state-of-the-art methods based on two different evaluations. We compared mGSZ results with permutation and rotation tests and show that rotation does not improve our asymptotic P-values. We also propose well-known asymptotic distribution models for three of the compared methods. mGSZ is available as R package from cran.r-project.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. α-Cut method based importance measure for criticality analysis in fuzzy probability – Based fault tree analysis

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry; Sony Tjahyani, D.T.; Widodo, Surip; Tjahjono, Hendro

    2017-01-01

    Highlights: •FPFTA deals with epistemic uncertainty using fuzzy probability. •Criticality analysis is important for reliability improvement. •An α-cut method based importance measure is proposed for criticality analysis in FPFTA. •The α-cut method based importance measure utilises α-cut multiplication, α-cut subtraction, and area defuzzification technique. •Benchmarking confirm that the proposed method is feasible for criticality analysis in FPFTA. -- Abstract: Fuzzy probability – based fault tree analysis (FPFTA) has been recently developed and proposed to deal with the limitations of conventional fault tree analysis. In FPFTA, reliabilities of basic events, intermediate events and top event are characterized by fuzzy probabilities. Furthermore, the quantification of the FPFTA is based on fuzzy multiplication rule and fuzzy complementation rule to propagate uncertainties from basic event to the top event. Since the objective of the fault tree analysis is to improve the reliability of the system being evaluated, it is necessary to find the weakest path in the system. For this purpose, criticality analysis can be implemented. Various importance measures, which are based on conventional probabilities, have been developed and proposed for criticality analysis in fault tree analysis. However, not one of those importance measures can be applied for criticality analysis in FPFTA, which is based on fuzzy probability. To be fully applied in nuclear power plant probabilistic safety assessment, FPFTA needs to have its corresponding importance measure. The objective of this study is to develop an α-cut method based importance measure to evaluate and rank the importance of basic events for criticality analysis in FPFTA. To demonstrate the applicability of the proposed measure, a case study is performed and its results are then benchmarked to the results generated by the four well known importance measures in conventional fault tree analysis. The results

  2. Infrared dim small target segmentation method based on ALI-PCNN model

    Science.gov (United States)

    Zhao, Shangnan; Song, Yong; Zhao, Yufei; Li, Yun; Li, Xu; Jiang, Yurong; Li, Lin

    2017-10-01

    Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

  3. Phase difference estimation method based on data extension and Hilbert transform

    International Nuclear Information System (INIS)

    Shen, Yan-lin; Tu, Ya-qing; Chen, Lin-jun; Shen, Ting-ao

    2015-01-01

    To improve the precision and anti-interference performance of phase difference estimation for non-integer periods of sampling signals, a phase difference estimation method based on data extension and Hilbert transform is proposed. Estimated phase difference is obtained by means of data extension, Hilbert transform, cross-correlation, auto-correlation, and weighted phase average. Theoretical analysis shows that the proposed method suppresses the end effects of Hilbert transform effectively. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of phase difference estimation and has better performance of phase difference estimation than the correlation, Hilbert transform, and data extension-based correlation methods, which contribute to improving the measurement precision of the Coriolis mass flowmeter. (paper)

  4. The Simulation of the Recharging Method Based on Solar Radiation for an Implantable Biosensor.

    Science.gov (United States)

    Li, Yun; Song, Yong; Kong, Xianyue; Li, Maoyuan; Zhao, Yufei; Hao, Qun; Gao, Tianxin

    2016-09-10

    A method of recharging implantable biosensors based on solar radiation is proposed. Firstly, the models of the proposed method are developed. Secondly, the recharging processes based on solar radiation are simulated using Monte Carlo (MC) method and the energy distributions of sunlight within the different layers of human skin have been achieved and discussed. Finally, the simulation results are verified experimentally, which indicates that the proposed method will contribute to achieve a low-cost, convenient and safe method for recharging implantable biosensors.

  5. Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines

    Directory of Open Access Journals (Sweden)

    Boming Song

    2017-01-01

    Full Text Available Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS propagation error of the localization signal between the access point (AP and the target node (Tag. In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR method or received signal strength indication (RSSI based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

  6. AN OBJECT-BASED METHOD FOR CHINESE LANDFORM TYPES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Ding

    2016-06-01

    Full Text Available Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM. In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

  7. History based batch method preserving tally means

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Choi, Sung Hoon

    2012-01-01

    In the Monte Carlo (MC) eigenvalue calculations, the sample variance of a tally mean calculated from its cycle-wise estimates is biased because of the inter-cycle correlations of the fission source distribution (FSD). Recently, we proposed a new real variance estimation method named the history-based batch method in which a MC run is treated as multiple runs with small number of histories per cycle to generate independent tally estimates. In this paper, the history-based batch method based on the weight correction is presented to preserve the tally mean from the original MC run. The effectiveness of the new method is examined for the weakly coupled fissile array problem as a function of the dominance ratio and the batch size, in comparison with other schemes available

  8. A parallel orbital-updating based plane-wave basis method for electronic structure calculations

    International Nuclear Information System (INIS)

    Pan, Yan; Dai, Xiaoying; Gironcoli, Stefano de; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

    2017-01-01

    Highlights: • Propose three parallel orbital-updating based plane-wave basis methods for electronic structure calculations. • These new methods can avoid the generating of large scale eigenvalue problems and then reduce the computational cost. • These new methods allow for two-level parallelization which is particularly interesting for large scale parallelization. • Numerical experiments show that these new methods are reliable and efficient for large scale calculations on modern supercomputers. - Abstract: Motivated by the recently proposed parallel orbital-updating approach in real space method , we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

  9. Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

    Science.gov (United States)

    Omagari, Hiroki; Higashino, Shin-Ichiro

    2018-04-01

    In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

  10. A proposed assessment method for image of regional educational institutions

    Directory of Open Access Journals (Sweden)

    Kataeva Natalya

    2017-01-01

    Full Text Available Market of educational services in the current Russian economic conditions is a complex of a huge variety of educational institutions. Market of educational services is already experiencing a significant influence of the demographic situation in Russia. This means that higher education institutions are forced to fight in a tough competition for high school students. Increased competition in the educational market forces universities to find new methods of non-price competition in attraction of potential students and throughout own educational and economic activities. Commercialization of education places universities in a single plane with commercial companies who study a positive perception of the image and reputation as a competitive advantage, which is quite acceptable for use in strategic and current activities of higher education institutions to ensure the competitiveness of educational services and educational institution in whole. Nevertheless, due to lack of evidence-based proposals in this area there is a need for scientific research in terms of justification of organizational and methodological aspects of image use as a factor in the competitiveness of the higher education institution. Theoretically and practically there are different methods and ways of evaluating the company’s image. The article provides a comparative assessment of the existing valuation methods of corporate image and the author’s method of estimating the image of higher education institutions based on the key influencing factors. The method has been tested on the Vyatka State Agricultural Academy (Russia. The results also indicate the strengths and weaknesses of the institution, highlights ways of improving, and adjusts the efforts for image improvement.

  11. Drone-based Object Counting by Spatially Regularized Regional Proposal Network

    OpenAIRE

    Hsieh, Meng-Ru; Lin, Yen-Liang; Hsu, Winston H.

    2017-01-01

    Existing counting methods often adopt regression-based approaches and cannot precisely localize the target objects, which hinders the further analysis (e.g., high-level understanding and fine-grained classification). In addition, most of prior work mainly focus on counting objects in static environments with fixed cameras. Motivated by the advent of unmanned flying vehicles (i.e., drones), we are interested in detecting and counting objects in such dynamic environments. We propose Layout Prop...

  12. Real-time biscuit tile image segmentation method based on edge detection.

    Science.gov (United States)

    Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

    2018-05-01

    In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  13. An Automated Baseline Correction Method Based on Iterative Morphological Operations.

    Science.gov (United States)

    Chen, Yunliang; Dai, Liankui

    2018-05-01

    Raman spectra usually suffer from baseline drift caused by fluorescence or other reasons. Therefore, baseline correction is a necessary and crucial step that must be performed before subsequent processing and analysis of Raman spectra. An automated baseline correction method based on iterative morphological operations is proposed in this work. The method can adaptively determine the structuring element first and then gradually remove the spectral peaks during iteration to get an estimated baseline. Experiments on simulated data and real-world Raman data show that the proposed method is accurate, fast, and flexible for handling different kinds of baselines in various practical situations. The comparison of the proposed method with some state-of-the-art baseline correction methods demonstrates its advantages over the existing methods in terms of accuracy, adaptability, and flexibility. Although only Raman spectra are investigated in this paper, the proposed method is hopefully to be used for the baseline correction of other analytical instrumental signals, such as IR spectra and chromatograms.

  14. A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

    KAUST Repository

    Liang, Faming; Cheng, Yichen; Song, Qifan; Park, Jincheol; Yang, Ping

    2013-01-01

    large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate

  15. Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

    Science.gov (United States)

    Chiba, Shuntaro; Ikeda, Kazuyoshi; Ishida, Takashi; Gromiha, M Michael; Taguchi, Y-H; Iwadate, Mitsuo; Umeyama, Hideaki; Hsin, Kun-Yi; Kitano, Hiroaki; Yamamoto, Kazuki; Sugaya, Nobuyoshi; Kato, Koya; Okuno, Tatsuya; Chikenji, George; Mochizuki, Masahiro; Yasuo, Nobuaki; Yoshino, Ryunosuke; Yanagisawa, Keisuke; Ban, Tomohiro; Teramoto, Reiji; Ramakrishnan, Chandrasekaran; Thangakani, A Mary; Velmurugan, D; Prathipati, Philip; Ito, Junichi; Tsuchiya, Yuko; Mizuguchi, Kenji; Honma, Teruki; Hirokawa, Takatsugu; Akiyama, Yutaka; Sekijima, Masakazu

    2015-11-26

    A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

  16. Continuous energy Monte Carlo method based lattice homogeinzation

    International Nuclear Information System (INIS)

    Li Mancang; Yao Dong; Wang Kan

    2014-01-01

    Based on the Monte Carlo code MCNP, the continuous energy Monte Carlo multi-group constants generation code MCMC has been developed. The track length scheme has been used as the foundation of cross section generation. The scattering matrix and Legendre components require special techniques, and the scattering event method has been proposed to solve this problem. Three methods have been developed to calculate the diffusion coefficients for diffusion reactor core codes and the Legendre method has been applied in MCMC. To the satisfaction of the equivalence theory, the general equivalence theory (GET) and the superhomogenization method (SPH) have been applied to the Monte Carlo method based group constants. The super equivalence method (SPE) has been proposed to improve the equivalence. GET, SPH and SPE have been implemented into MCMC. The numerical results showed that generating the homogenization multi-group constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum, thus provides more accuracy parameters. Besides, the same code and data library can be used for a wide range of applications due to the versatility. The MCMC scheme can be seen as a potential alternative to the widely used deterministic lattice codes. (authors)

  17. Construction Method of Display Proposal for Commodities in Sales Promotion by Genetic Algorithm

    Science.gov (United States)

    Yumoto, Masaki

    In a sales promotion task, wholesaler prepares and presents the display proposal for commodities in order to negotiate with retailer's buyers what commodities they should sell. For automating the sales promotion tasks, the proposal has to be constructed according to the target retailer's buyer. However, it is difficult to construct the proposal suitable for the target retail store because of too much combination of commodities. This paper proposes a construction method by Genetic algorithm (GA). The proposed method represents initial display proposals for commodities with genes, improve ones with the evaluation value by GA, and rearrange one with the highest evaluation value according to the classification of commodity. Through practical experiment, we can confirm that display proposal by the proposed method is similar with the one constructed by a wholesaler.

  18. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  19. Trends and regional variations in provision of contraception methods in a commercially insured population in the United States based on nationally proposed measures.

    Science.gov (United States)

    Law, A; Yu, J S; Wang, W; Lin, J; Lynen, R

    2017-09-01

    Three measures to assess the provision of effective contraception methods among reproductive-aged women have recently been endorsed for national public reporting. Based on these measures, this study examined real-world trends and regional variations of contraceptive provision in a commercially insured population in the United States. Women 15-44years old with continuous enrollment in each year from 2005 to 2014 were identified from a commercial claims database. In accordance with the proposed measures, percentages of women (a) provided most effective or moderately effective (MEME) methods of contraception and (b) provided a long-acting reversible contraceptive (LARC) method were calculated in two populations: women at risk for unintended pregnancy and women who had a live birth within 3 and 60days of delivery. During the 10-year period, the percentages of women at risk for unintended pregnancy provided MEME contraceptive methods increased among 15-20-year-olds (24.5%-35.9%) and 21-44-year-olds (26.2%-31.5%), and those provided a LARC method also increased among 15-20-year-olds (0.1%-2.4%) and 21-44-year-olds (0.8%-3.9%). Provision of LARC methods increased most in the North Central and West among both age groups of women. Provision of MEME contraceptives and LARC methods to women who had a live birth within 60days postpartum also increased across age groups and regions. This assessment indicates an overall trend of increasing provision of MEME contraceptive methods in the commercial sector, albeit with age group and regional variations. If implemented, these proposed measures may have impacts on health plan contraceptive access policy. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Novel X-ray Communication Based XNAV Augmentation Method Using X-ray Detectors

    Directory of Open Access Journals (Sweden)

    Shibin Song

    2015-09-01

    Full Text Available The further development of X-ray pulsar-based NAVigation (XNAV is hindered by its lack of accuracy, so accuracy improvement has become a critical issue for XNAV. In this paper, an XNAV augmentation method which utilizes both pulsar observation and X-ray ranging observation for navigation filtering is proposed to deal with this issue. As a newly emerged concept, X-ray communication (XCOM shows great potential in space exploration. X-ray ranging, derived from XCOM, could achieve high accuracy in range measurement, which could provide accurate information for XNAV. For the proposed method, the measurement models of pulsar observation and range measurement observation are established, and a Kalman filtering algorithm based on the observations and orbit dynamics is proposed to estimate the position and velocity of a spacecraft. A performance comparison of the proposed method with the traditional pulsar observation method is conducted by numerical experiments. Besides, the parameters that influence the performance of the proposed method, such as the pulsar observation time, the SNR of the ranging signal, etc., are analyzed and evaluated by numerical experiments.

  1. Level set method for image segmentation based on moment competition

    Science.gov (United States)

    Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

    2015-05-01

    We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

  2. Description logic-based methods for auditing frame-based medical terminological systems.

    Science.gov (United States)

    Cornet, Ronald; Abu-Hanna, Ameen

    2005-07-01

    Medical terminological systems (TSs) play an increasingly important role in health care by supporting recording, retrieval and analysis of patient information. As the size and complexity of TSs are growing, the need arises for means to audit them, i.e. verify and maintain (logical) consistency and (semantic) correctness of their contents. This is not only important for the management of TSs but also for providing their users with confidence about the reliability of their contents. Formal methods have the potential to play an important role in the audit of TSs, although there are few empirical studies to assess the benefits of using these methods. In this paper we propose a method based on description logics (DLs) for the audit of TSs. This method is based on the migration of the medical TS from a frame-based representation to a DL-based one. Our method is characterized by a process in which initially stringent assumptions are made about concept definitions. The assumptions allow the detection of concepts and relations that might comprise a source of logical inconsistency. If the assumptions hold then definitions are to be altered to eliminate the inconsistency, otherwise the assumptions are revised. In order to demonstrate the utility of the approach in a real-world case study we audit a TS in the intensive care domain and discuss decisions pertaining to building DL-based representations. This case study demonstrates that certain types of inconsistencies can indeed be detected by applying the method to a medical terminological system. The added value of the method described in this paper is that it provides a means to evaluate the compliance to a number of common modeling principles in a formal manner. The proposed method reveals potential modeling inconsistencies, helping to audit and (if possible) improve the medical TS. In this way, it contributes to providing confidence in the contents of the terminological system.

  3. Proposal for outline of training and evaluation method for non-technical skills

    International Nuclear Information System (INIS)

    Nagasaka, Akihiko; Shibue, Hisao

    2015-01-01

    The purpose of this study is to systematize measures for improvement of emergency response capability focused on non-technical skills. As the results of investigation of some emergency training in nuclear power plant and referring to CRM training, following two issues were picked up. 1) Lack of practical training method for improvement of non-technical skills. 2) Lack of evaluation method of non-technical skills. Then, based on these 7 non-technical skills 'situational awareness' 'decision making' 'communication' 'teamworking' 'leadership' 'managing stress' 'coping with fatigue' are promotion factors to improve emergency response capability, we propose practical training method for each non-technical skill. Also we give example of behavioral markers as evaluation factor, and indicate approaches to introduce the evaluation method of non-technical skills. (author)

  4. A Method for Proposing Valued-Adding Attributes in Customized Housing

    Directory of Open Access Journals (Sweden)

    Cynthia S. Hentschke

    2014-12-01

    Full Text Available In most emerging economies, there has been many incentives and high availability of funding for low-cost housing projects. This has encouraged product standardization and the application of mass production ideas, based on the assumption that this is the most effective strategy for reducing costs. However, the delivery of highly standardized housing units to customers with different needs, without considering their lifestyle and perception of value, often results in inadequate products. Mass customization has been pointed out as an effective strategy to improve value generation in low-cost housing projects, and to avoid waste caused by renovations done in dwellings soon after occupancy. However, one of the main challenges for the implementation of mass customization is the definition of a set of relevant options based on users’ perceived value. The aim of this paper is to propose a method for defining value adding attributes in customized housing projects, which can support decision-making in product development. The means-end chain theory was used as theoretical framework to connect product attributes and costumers’ values, through the application of the laddering technique. The method was tested in two house-building projects delivered by a company from Brazil. The main contribution of this method is to indicate the customization units that are most important for users along with the explanation of why those units are the most relevant ones.

  5. Control method for biped locomotion robots based on ZMP information

    International Nuclear Information System (INIS)

    Kume, Etsuo

    1994-01-01

    The Human Acts Simulation Program (HASP) started as a ten year program of Computing and Information Systems Center (CISC) at Japan Atomic Energy Research Institute (JAERI) in 1987. A mechanical design study of biped locomotion robots for patrol and inspection in nuclear facilities is being performed as an item of the research scope. One of the goals of our research is to design a biped locomotion robot for practical use in nuclear facilities. So far, we have been studying for several dynamic walking patterns. In conventional control methods for biped locomotion robots, the program control is used based on preset walking patterns, so it dose not have the robustness such as a dynamic change of walking pattern. Therefore, a real-time control method based on dynamic information of the robot states is necessary for the high performance of walking. In this study a new control method based on Zero Moment Point (ZMP) information is proposed as one of real-time control methods. The proposed method is discussed and validated based on the numerical simulation. (author)

  6. Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

    Science.gov (United States)

    Jones, Harry

    2005-01-01

    The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation

  7. Proposed Doctrine Based Structure of the Armored Reconnaissance Squadron

    Science.gov (United States)

    2017-06-09

    squadron. A new structure was proposed based on the deduced required capabilities, utilizing organizational theory and current army practices. This...squadron, which now puts greater emphasis on this analysis to link structure to doctrinally based task. Organizational Theory Since earliest...expect to find capability based discourse; there is a lack of proposed structure based on capability, task or equipment . The Armour Bulletin serves

  8. A prediction method based on grey system theory in equipment condition based maintenance

    International Nuclear Information System (INIS)

    Yan, Shengyuan; Yan, Shengyuan; Zhang, Hongguo; Zhang, Zhijian; Peng, Minjun; Yang, Ming

    2007-01-01

    Grey prediction is a modeling method based on historical or present, known or indefinite information, which can be used for forecasting the development of the eigenvalues of the targeted equipment system and setting up the model by using less information. In this paper, the postulate of grey system theory, which includes the grey generating, the sorts of grey generating and the grey forecasting model, is introduced first. The concrete application process, which includes the grey prediction modeling, grey prediction, error calculation, equal dimension and new information approach, is introduced secondly. Application of a so-called 'Equal Dimension and New Information' (EDNI) technology in grey system theory is adopted in an application case, aiming at improving the accuracy of prediction without increasing the amount of calculation by replacing old data with new ones. The proposed method can provide a new way for solving the problem of eigenvalue data exploding in equal distance effectively, short time interval and real time prediction. The proposed method, which was based on historical or present, known or indefinite information, was verified by the vibration prediction of induced draft fan of a boiler of the Yantai Power Station in China, and the results show that the proposed method based on grey system theory is simple and provides a high accuracy in prediction. So, it is very useful and significant to the controlling and controllable management in safety production. (authors)

  9. A rule-based automatic sleep staging method.

    Science.gov (United States)

    Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

    2012-03-30

    In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. A Multiple Criteria Decision Making Method Based on Relative Value Distances

    Directory of Open Access Journals (Sweden)

    Shyur Huan-jyh

    2015-12-01

    Full Text Available This paper proposes a new multiple criteria decision-making method called ERVD (election based on relative value distances. The s-shape value function is adopted to replace the expected utility function to describe the risk-averse and risk-seeking behavior of decision makers. Comparisons and experiments contrasting with the TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution method are carried out to verify the feasibility of using the proposed method to represent the decision makers’ preference in the decision making process. Our experimental results show that the proposed approach is an appropriate and effective MCDM method.

  11. Interlaboratory diagnostic accuracy of a Salmonella specific PCR-based method

    DEFF Research Database (Denmark)

    Malorny, B.; Hoorfar, Jeffrey; Hugas, M.

    2003-01-01

    A collaborative study involving four European laboratories was conducted to investigate the diagnostic accuracy of a Salmonella specific PCR-based method, which was evaluated within the European FOOD-PCR project (http://www.pcr.dk). Each laboratory analysed by the PCR a set of independent obtained...... presumably naturally contaminated samples and compared the results with the microbiological culture method. The PCR-based method comprised a preenrichment step in buffered peptone water followed by a thermal cell lysis using a closed tube resin-based method. Artificially contaminated minced beef and whole......-based diagnostic methods and is currently proposed as international standard document....

  12. Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

    Science.gov (United States)

    Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

    2017-08-01

    In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

  13. Distance Based Method for Outlier Detection of Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haibin Zhang

    2016-01-01

    Full Text Available We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate.

  14. Systematic review of proposed definitions of nocturnal polyuria and population-based evidence of their diagnostic accuracy.

    Science.gov (United States)

    Olesen, Tine Kold; Denys, Marie-Astrid; Vande Walle, Johan; Everaert, Karel

    2018-02-06

    Background Evidence of diagnostic accuracy for proposed definitions of nocturnal polyuria is currently unclear. Purpose Systematic review to determine population-based evidence of the diagnostic accuracy of proposed definitions of nocturnal polyuria based on data from frequency-volume charts. Methods Seventeen pre-specified search terms identified 351 unique investigations published from 1990 to 2016 in BIOSIS, Embase, Embase Alerts, International Pharmaceutical Abstract, Medline, and Cochrane. Thirteen original communications were included in this review based on pre-specified exclusion criteria. Data were extracted from each paper regarding subject age, sex, ethnicity, health status, sample size, data collection methods, and diagnostic discrimination of proposed definitions including sensitivity, specificity, positive and negative predictive value. Results The sample size of study cohorts, participant age, sex, ethnicity, and health status varied considerably in 13 studies reporting on the diagnostic performance of seven different definitions of nocturnal polyuria using frequency-volume chart data from 4968 participants. Most study cohorts were small, mono-ethnic, including only Caucasian males aged 50 or higher with primary or secondary polyuria that were compared to a control group of healthy men without nocturia in prospective or retrospective settings. Proposed definitions had poor discriminatory accuracy in evaluations based on data from subjects independent from the original study cohorts with findings being similar regarding the most widely evaluated definition endorsed by ICS. Conclusions Diagnostic performance characteristics for proposed definitions of nocturnal polyuria show poor to modest discrimination and are not based on sufficient level of evidence from representative, multi-ethnic population-based data from both females and males of all adult ages.

  15. A circular feature-based pose measurement method for metal part grasping

    International Nuclear Information System (INIS)

    Wu, Chenrui; He, Zaixing; Zhang, Shuyou; Zhao, Xinyue

    2017-01-01

    The grasping of circular metal parts such as bearings and flanges is a common task in industry. Limited by low texture and repeated features, the point-feature-based method is not applicable in pose measurement of these parts. In this paper, we propose a novel pose measurement method for grasping circular metal parts. This method is based on cone degradation and involves a monocular camera. To achieve higher measurement accuracy, a position-based visual servoing method is presented to continuously control an eye-in-hand, six-degrees-of-freedom robot arm to grasp the part. The uncertainty of the part’s coordinate frame during the control process is solved by defining a fixed virtual coordinate frame. Experimental results are provided to illustrate the effectiveness of the proposed method and the factors that affect measurement accuracy are analyzed. (paper)

  16. A Statistic-Based Calibration Method for TIADC System

    Directory of Open Access Journals (Sweden)

    Kuojun Yang

    2015-01-01

    Full Text Available Time-interleaved technique is widely used to increase the sampling rate of analog-to-digital converter (ADC. However, the channel mismatches degrade the performance of time-interleaved ADC (TIADC. Therefore, a statistic-based calibration method for TIADC is proposed in this paper. The average value of sampling points is utilized to calculate offset error, and the summation of sampling points is used to calculate gain error. After offset and gain error are obtained, they are calibrated by offset and gain adjustment elements in ADC. Timing skew is calibrated by an iterative method. The product of sampling points of two adjacent subchannels is used as a metric for calibration. The proposed method is employed to calibrate mismatches in a four-channel 5 GS/s TIADC system. Simulation results show that the proposed method can estimate mismatches accurately in a wide frequency range. It is also proved that an accurate estimation can be obtained even if the signal noise ratio (SNR of input signal is 20 dB. Furthermore, the results obtained from a real four-channel 5 GS/s TIADC system demonstrate the effectiveness of the proposed method. We can see that the spectra spurs due to mismatches have been effectively eliminated after calibration.

  17. Distant Supervision for Relation Extraction with Ranking-Based Methods

    Directory of Open Access Journals (Sweden)

    Yang Xiang

    2016-05-01

    Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

  18. Digital Image Stabilization Method Based on Variational Mode Decomposition and Relative Entropy

    Directory of Open Access Journals (Sweden)

    Duo Hao

    2017-11-01

    Full Text Available Cameras mounted on vehicles frequently suffer from image shake due to the vehicles’ motions. To remove jitter motions and preserve intentional motions, a hybrid digital image stabilization method is proposed that uses variational mode decomposition (VMD and relative entropy (RE. In this paper, the global motion vector (GMV is initially decomposed into several narrow-banded modes by VMD. REs, which exhibit the difference of probability distribution between two modes, are then calculated to identify the intentional and jitter motion modes. Finally, the summation of the jitter motion modes constitutes jitter motions, whereas the subtraction of the resulting sum from the GMV represents the intentional motions. The proposed stabilization method is compared with several known methods, namely, medium filter (MF, Kalman filter (KF, wavelet decomposition (MD method, empirical mode decomposition (EMD-based method, and enhanced EMD-based method, to evaluate stabilization performance. Experimental results show that the proposed method outperforms the other stabilization methods.

  19. FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Zhao

    2017-09-01

    Full Text Available The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

  20. A Novel Assembly Line Balancing Method Based on PSO Algorithm

    Directory of Open Access Journals (Sweden)

    Xiaomei Hu

    2014-01-01

    Full Text Available Assembly line is widely used in manufacturing system. Assembly line balancing problem is a crucial question during design and management of assembly lines since it directly affects the productivity of the whole manufacturing system. The model of assembly line balancing problem is put forward and a general optimization method is proposed. The key data on assembly line balancing problem is confirmed, and the precedence relations diagram is described. A double objective optimization model based on takt time and smoothness index is built, and balance optimization scheme based on PSO algorithm is proposed. Through the simulation experiments of examples, the feasibility and validity of the assembly line balancing method based on PSO algorithm is proved.

  1. Developing a Self-Report-Based Sequential Analysis Method for Educational Technology Systems: A Process-Based Usability Evaluation

    Science.gov (United States)

    Lin, Yi-Chun; Hsieh, Ya-Hui; Hou, Huei-Tse

    2015-01-01

    The development of a usability evaluation method for educational systems or applications, called the self-report-based sequential analysis, is described herein. The method aims to extend the current practice by proposing self-report-based sequential analysis as a new usability method, which integrates the advantages of self-report in survey…

  2. Hyperspectral image compressing using wavelet-based method

    Science.gov (United States)

    Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

    2017-10-01

    Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

  3. Proposal of evaluation method of tsunami wave pressure using 2D depth-integrated flow simulation

    International Nuclear Information System (INIS)

    Arimitsu, Tsuyoshi; Ooe, Kazuya; Kawasaki, Koji

    2012-01-01

    To design and construct land structures resistive to tsunami force, it is most essential to evaluate tsunami pressure quantitatively. The existing hydrostatic formula, in general, tended to underestimate tsunami wave pressure under the condition of inundation flow with large Froude number. Estimation method of tsunami pressure acting on a land structure was proposed using inundation depth and horizontal velocity at the front of the structure, which were calculated employing a 2D depth-integrated flow model based on the unstructured grid system. The comparison between the numerical and experimental results revealed that the proposed method could reasonably reproduce the vertical distribution of the maximum tsunami pressure as well as the time variation of the tsunami pressure exerting on the structure. (author)

  4. RESEARCH ON KNOWLEDGE-BASED OPTIMIZATION METHOD OF INDOOR LOCATION BASED ON LOW ENERGY BLUETOOTH

    Directory of Open Access Journals (Sweden)

    C. Li

    2017-09-01

    Full Text Available With the rapid development of LBS (Location-based Service, the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1 The establishment and application of a priori and posterior knowledge base. 2 Primary selection of signal source. 3 Elimination of positioning gross error. 4 Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

  5. Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth

    Science.gov (United States)

    Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.

    2017-09-01

    With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

  6. An Initialization Method Based on Hybrid Distance for k-Means Algorithm.

    Science.gov (United States)

    Yang, Jie; Ma, Yan; Zhang, Xiangfen; Li, Shunbao; Zhang, Yuping

    2017-11-01

    The traditional [Formula: see text]-means algorithm has been widely used as a simple and efficient clustering method. However, the performance of this algorithm is highly dependent on the selection of initial cluster centers. Therefore, the method adopted for choosing initial cluster centers is extremely important. In this letter, we redefine the density of points according to the number of its neighbors, as well as the distance between points and their neighbors. In addition, we define a new distance measure that considers both Euclidean distance and density. Based on that, we propose an algorithm for selecting initial cluster centers that can dynamically adjust the weighting parameter. Furthermore, we propose a new internal clustering validation measure, the clustering validation index based on the neighbors (CVN), which can be exploited to select the optimal result among multiple clustering results. Experimental results show that the proposed algorithm outperforms existing initialization methods on real-world data sets and demonstrates the adaptability of the proposed algorithm to data sets with various characteristics.

  7. Interchange Recognition Method Based on CNN

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2018-03-01

    Full Text Available The identification and classification of interchange structures in OSM data can provide important information for the construction of multi-scale model, navigation and location services, congestion analysis, etc. The traditional method of interchange identification relies on the low-level characteristics of artificial design, and cannot distinguish the complex interchange structure with interference section effectively. In this paper, a new method based on convolutional neural network for identification of the interchange is proposed. The method combines vector data with raster image, and uses neural network to learn the fuzzy characteristics of the interchange, and classifies the complex interchange structure in OSM. Experiments show that this method has strong anti-interference, and has achieved good results in the classification of complex interchange shape, and there is room for further improvement with the expansion of the case base and the optimization of neural network model.

  8. Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory

    Directory of Open Access Journals (Sweden)

    Feng Hu

    2012-01-01

    Full Text Available The divide and conquer method is a typical granular computing method using multiple levels of abstraction and granulations. So far, although some achievements based on divided and conquer method in the rough set theory have been acquired, the systematic methods for knowledge reduction based on divide and conquer method are still absent. In this paper, the knowledge reduction approaches based on divide and conquer method, under equivalence relation and under tolerance relation, are presented, respectively. After that, a systematic approach, named as the abstract process for knowledge reduction based on divide and conquer method in rough set theory, is proposed. Based on the presented approach, two algorithms for knowledge reduction, including an algorithm for attribute reduction and an algorithm for attribute value reduction, are presented. Some experimental evaluations are done to test the methods on uci data sets and KDDCUP99 data sets. The experimental results illustrate that the proposed approaches are efficient to process large data sets with good recognition rate, compared with KNN, SVM, C4.5, Naive Bayes, and CART.

  9. Performance-based parameter tuning method of model-driven PID control systems.

    Science.gov (United States)

    Zhao, Y M; Xie, W F; Tu, X W

    2012-05-01

    In this paper, performance-based parameter tuning method of model-driven Two-Degree-of-Freedom PID (MD TDOF PID) control system has been proposed to enhance the control performances of a process. Known for its ability of stabilizing the unstable processes, fast tracking to the change of set points and rejecting disturbance, the MD TDOF PID has gained research interest recently. The tuning methods for the reported MD TDOF PID are based on internal model control (IMC) method instead of optimizing the performance indices. In this paper, an Integral of Time Absolute Error (ITAE) zero-position-error optimal tuning and noise effect minimizing method is proposed for tuning two parameters in MD TDOF PID control system to achieve the desired regulating and disturbance rejection performance. The comparison with Two-Degree-of-Freedom control scheme by modified smith predictor (TDOF CS MSP) and the designed MD TDOF PID tuned by the IMC tuning method demonstrates the effectiveness of the proposed tuning method. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Traffic speed data imputation method based on tensor completion.

    Science.gov (United States)

    Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

    2015-01-01

    Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

  11. Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seunggyu [Korea Aerospace Research Institue, Daejeon (Korea, Republic of); Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

    2017-05-15

    The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

  12. Correcting for cryptic relatedness by a regression-based genomic control method

    Directory of Open Access Journals (Sweden)

    Yang Yaning

    2009-12-01

    Full Text Available Abstract Background Genomic control (GC method is a useful tool to correct for the cryptic relatedness in population-based association studies. It was originally proposed for correcting for the variance inflation of Cochran-Armitage's additive trend test by using information from unlinked null markers, and was later generalized to be applicable to other tests with the additional requirement that the null markers are matched with the candidate marker in allele frequencies. However, matching allele frequencies limits the number of available null markers and thus limits the applicability of the GC method. On the other hand, errors in genotype/allele frequencies may cause further bias and variance inflation and thereby aggravate the effect of GC correction. Results In this paper, we propose a regression-based GC method using null markers that are not necessarily matched in allele frequencies with the candidate marker. Variation of allele frequencies of the null markers is adjusted by a regression method. Conclusion The proposed method can be readily applied to the Cochran-Armitage's trend tests other than the additive trend test, the Pearson's chi-square test and other robust efficiency tests. Simulation results show that the proposed method is effective in controlling type I error in the presence of population substructure.

  13. IWKNN: An Effective Bluetooth Positioning Method Based on Isomap and WKNN

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2016-01-01

    Full Text Available Recently, Bluetooth-based indoor positioning has become a hot research topic. However, the instability of Bluetooth RSSI (Received Signal Strength Indicator promotes a huge challenge in localization accuracy. To improve the localization accuracy, this paper measures the distance of RSSI vectors on their low-dimensional manifold and proposes a novel positioning method IWKNN (Isomap-based Weighted K-Nearest Neighbor. The proposed method firstly uses Isomap to generate low-dimensional embedding for RSSI vectors. Then, the distance of two given RSSI vectors is measured by Euclidean distance of their low-dimensional embeddings. Finally, the position is calculated by WKNN. Experiment indicates that the proposed approach is more robust and accurate.

  14. A Proposed Stochastic Finite Difference Approach Based on Homogenous Chaos Expansion

    Directory of Open Access Journals (Sweden)

    O. H. Galal

    2013-01-01

    Full Text Available This paper proposes a stochastic finite difference approach, based on homogenous chaos expansion (SFDHC. The said approach can handle time dependent nonlinear as well as linear systems with deterministic or stochastic initial and boundary conditions. In this approach, included stochastic parameters are modeled as second-order stochastic processes and are expanded using Karhunen-Loève expansion, while the response function is approximated using homogenous chaos expansion. Galerkin projection is used in converting the original stochastic partial differential equation (PDE into a set of coupled deterministic partial differential equations and then solved using finite difference method. Two well-known equations were used for efficiency validation of the method proposed. First one being the linear diffusion equation with stochastic parameter and the second is the nonlinear Burger's equation with stochastic parameter and stochastic initial and boundary conditions. In both of these examples, the probability distribution function of the response manifested close conformity to the results obtained from Monte Carlo simulation with optimized computational cost.

  15. Global positioning method based on polarized light compass system

    Science.gov (United States)

    Liu, Jun; Yang, Jiangtao; Wang, Yubo; Tang, Jun; Shen, Chong

    2018-05-01

    This paper presents a global positioning method based on a polarized light compass system. A main limitation of polarization positioning is the environment such as weak and locally destroyed polarization environments, and the solution to the positioning problem is given in this paper which is polarization image de-noising and segmentation. Therefore, the pulse coupled neural network is employed for enhancing positioning performance. The prominent advantages of the present positioning technique are as follows: (i) compared to the existing position method based on polarized light, better sun tracking accuracy can be achieved and (ii) the robustness and accuracy of positioning under weak and locally destroyed polarization environments, such as cloudy or building shielding, are improved significantly. Finally, some field experiments are given to demonstrate the effectiveness and applicability of the proposed global positioning technique. The experiments have shown that our proposed method outperforms the conventional polarization positioning method, the real time longitude and latitude with accuracy up to 0.0461° and 0.0911°, respectively.

  16. A qualitative method proposal to improve environmental impact assessment

    International Nuclear Information System (INIS)

    Toro, Javier; Requena, Ignacio; Duarte, Oscar; Zamorano, Montserrat

    2013-01-01

    In environmental impact assessment, qualitative methods are used because they are versatile and easy to apply. This methodology is based on the evaluation of the strength of the impact by grading a series of qualitative attributes that can be manipulated by the evaluator. The results thus obtained are not objective, and all too often impacts are eliminated that should be mitigated with corrective measures. However, qualitative methodology can be improved if the calculation of Impact Importance is based on the characteristics of environmental factors and project activities instead on indicators assessed by evaluators. In this sense, this paper proposes the inclusion of the vulnerability of environmental factors and the potential environmental impact of project activities. For this purpose, the study described in this paper defined Total Impact Importance and specified a quantification procedure. The results obtained in the case study of oil drilling in Colombia reflect greater objectivity in the evaluation of impacts as well as a positive correlation between impact values, the environmental characteristics at and near the project location, and the technical characteristics of project activities. -- Highlights: • Concept of vulnerability has been used to calculate the importance impact assessment. • This paper defined Total Impact Importance and specified a quantification procedure. • The method includes the characteristics of environmental and project activities. • The application has shown greater objectivity in the evaluation of impacts. • Better correlation between impact values, environment and the project has been shown

  17. A qualitative method proposal to improve environmental impact assessment

    Energy Technology Data Exchange (ETDEWEB)

    Toro, Javier, E-mail: jjtoroca@unal.edu.co [Institute of Environmental Studies, National University of Colombia at Bogotá (Colombia); Requena, Ignacio, E-mail: requena@decsai.ugr.es [Department of Computer Science and Artificial Intelligence, University of Granada (Spain); Duarte, Oscar, E-mail: ogduartev@unal.edu.co [National University of Colombia at Bogotá, Department of Electrical Engineering and Electronics (Colombia); Zamorano, Montserrat, E-mail: zamorano@ugr.es [Department of Civil Engineering, University of Granada (Spain)

    2013-11-15

    In environmental impact assessment, qualitative methods are used because they are versatile and easy to apply. This methodology is based on the evaluation of the strength of the impact by grading a series of qualitative attributes that can be manipulated by the evaluator. The results thus obtained are not objective, and all too often impacts are eliminated that should be mitigated with corrective measures. However, qualitative methodology can be improved if the calculation of Impact Importance is based on the characteristics of environmental factors and project activities instead on indicators assessed by evaluators. In this sense, this paper proposes the inclusion of the vulnerability of environmental factors and the potential environmental impact of project activities. For this purpose, the study described in this paper defined Total Impact Importance and specified a quantification procedure. The results obtained in the case study of oil drilling in Colombia reflect greater objectivity in the evaluation of impacts as well as a positive correlation between impact values, the environmental characteristics at and near the project location, and the technical characteristics of project activities. -- Highlights: • Concept of vulnerability has been used to calculate the importance impact assessment. • This paper defined Total Impact Importance and specified a quantification procedure. • The method includes the characteristics of environmental and project activities. • The application has shown greater objectivity in the evaluation of impacts. • Better correlation between impact values, environment and the project has been shown.

  18. Mutton Traceability Method Based on Internet of Things

    Directory of Open Access Journals (Sweden)

    Wu Min-Ning

    2014-01-01

    Full Text Available In order to improve the mutton traceability efficiency for Internet of Things and solve the problem of data transmission, analyzed existing tracking algorithm, proposed the food traceability application model, Petri network model of food traceability and food traceability of time series data of improved K-means algorithm based on the Internet of things. The food traceability application model to convert, integrate and mine the heterogeneous information, implementation of the food safety traceability information management, Petri network model for food traceability in the process of the state transition were analyzed and simulated and provides a theoretical basis to study the behavior described in the food traceability system and structural design. The experiments on simulation data show that the proposed traceability method based on Internet of Things is more effective for mutton traceability data than the traditional K-means methods.

  19. Damage evaluation by a guided wave-hidden Markov model based method

    Science.gov (United States)

    Mei, Hanfei; Yuan, Shenfang; Qiu, Lei; Zhang, Jinjin

    2016-02-01

    Guided wave based structural health monitoring has shown great potential in aerospace applications. However, one of the key challenges of practical engineering applications is the accurate interpretation of the guided wave signals under time-varying environmental and operational conditions. This paper presents a guided wave-hidden Markov model based method to improve the damage evaluation reliability of real aircraft structures under time-varying conditions. In the proposed approach, an HMM based unweighted moving average trend estimation method, which can capture the trend of damage propagation from the posterior probability obtained by HMM modeling is used to achieve a probabilistic evaluation of the structural damage. To validate the developed method, experiments are performed on a hole-edge crack specimen under fatigue loading condition and a real aircraft wing spar under changing structural boundary conditions. Experimental results show the advantage of the proposed method.

  20. Semantic text relatedness on Al-Qur’an translation using modified path based method

    Science.gov (United States)

    Irwanto, Yudi; Arif Bijaksana, Moch; Adiwijaya

    2018-03-01

    Abdul Baquee Muhammad [1] have built Corpus that contained AlQur’an domain, WordNet and dictionary. He has did initialisation in the development of knowledges about AlQur’an and the knowledges about relatedness between texts in AlQur’an. The Path based measurement method that proposed by Liu, Zhou and Zheng [3] has never been used in the AlQur’an domain. By using AlQur’an translation dataset in this research, the path based measurement method proposed by Liu, Zhou and Zheng [3] will be used to test this method in AlQur’an domain to obtain similarity values and to measure its correlation value. In this study the degree value is proposed to be used in modifying the path based method that proposed in previous research. Degree Value is the number of links that owned by a lcs (lowest common subsumer) node on a taxonomy. The links owned by a node on the taxonomy represent the semantic relationship that a node has in the taxonomy. By using degree value to modify the path-based method that proposed in previous research is expected that the correlation value obtained will increase. After running some experiment by using proposed method, the correlation measurement value can obtain fairly good correlation ties with 200 Word Pairs derive from Noun POS SimLex-999. The correlation value that be obtained is 93.3% which means their bonds are strong and they have very strong correlation. Whereas for the POS other than Noun POS vocabulary that owned by WordNet is incomplete therefore many pairs of words that the value of its similarity is zero so the correlation value is low.

  1. Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

    KAUST Repository

    Asiri, Sharefa M.

    2016-10-20

    In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear in unknown parameters. The well-posedness of the modulating functions-based solution is proved. The wave and the fifth-order KdV equations are used as examples to show the effectiveness of the proposed method in both noise-free and noisy cases.

  2. Recommendation advertising method based on behavior retargeting

    Science.gov (United States)

    Zhao, Yao; YIN, Xin-Chun; CHEN, Zhi-Min

    2011-10-01

    Online advertising has become an important business in e-commerce. Ad recommended algorithms are the most critical part in recommendation systems. We propose a recommendation advertising method based on behavior retargeting which can avoid leakage click of advertising due to objective reasons and can observe the changes of the user's interest in time. Experiments show that our new method can have a significant effect and can be further to apply to online system.

  3. 48 CFR 452.216-71 - Base Fee and Award Fee Proposal.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Base Fee and Award Fee... Base Fee and Award Fee Proposal. As prescribed in 416.470, insert the following provision: Base Fee and Award Proposal (FEB 1988) For the purpose of this solicitation, offerors shall propose a base fee of...

  4. A flocking based method for brain tractography.

    Science.gov (United States)

    Aranda, Ramon; Rivera, Mariano; Ramirez-Manzanares, Alonso

    2014-04-01

    We propose a new method to estimate axonal fiber pathways from Multiple Intra-Voxel Diffusion Orientations. Our method uses the multiple local orientation information for leading stochastic walks of particles. These stochastic particles are modeled with mass and thus they are subject to gravitational and inertial forces. As result, we obtain smooth, filtered and compact trajectory bundles. This gravitational interaction can be seen as a flocking behavior among particles that promotes better and robust axon fiber estimations because they use collective information to move. However, the stochastic walks may generate paths with low support (outliers), generally associated to incorrect brain connections. In order to eliminate the outlier pathways, we propose a filtering procedure based on principal component analysis and spectral clustering. The performance of the proposal is evaluated on Multiple Intra-Voxel Diffusion Orientations from two realistic numeric diffusion phantoms and a physical diffusion phantom. Additionally, we qualitatively demonstrate the performance on in vivo human brain data. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Visual assessment of BIPV retrofit design proposals for selected historical buildings using the saliency map method

    Directory of Open Access Journals (Sweden)

    Ran Xu

    2015-06-01

    Full Text Available With the increasing awareness of energy efficiency, many old buildings have to undergo a massive facade energy retrofit. How to predict the visual impact which solar installations on the aesthetic cultural value of these buildings has been a heated debate in Switzerland (and throughout the world. The usual evaluation method to describe the visual impact of BIPV is based on semantic and qualitative descriptors, and strongly dependent on personal preferences. The evaluation scale is therefore relative, flexible and imprecise. This paper proposes a new method to accurately measure the visual impact which BIPV installations have on a historical building by using the saliency map method. By imitating working principles of the human eye, it is measured how much the BIPV design proposals differ from the original building facade in the aspect of attracting human visual attention. The result is directly presented in a quantitative manner, and can be used to compare the fitness of different BIPV design proposals. The measuring process is numeric, objective and more precise.  

  6. Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study

    International Nuclear Information System (INIS)

    Zhai, Qingqing; Yang, Jun; Zhao, Yu

    2014-01-01

    Variance-based sensitivity analysis has been widely studied and asserted itself among practitioners. Monte Carlo simulation methods are well developed in the calculation of variance-based sensitivity indices but they do not make full use of each model run. Recently, several works mentioned a scatter-plot partitioning method to estimate the variance-based sensitivity indices from given data, where a single bunch of samples is sufficient to estimate all the sensitivity indices. This paper focuses on the space-partition method in the estimation of variance-based sensitivity indices, and its convergence and other performances are investigated. Since the method heavily depends on the partition scheme, the influence of the partition scheme is discussed and the optimal partition scheme is proposed based on the minimized estimator's variance. A decomposition and integration procedure is proposed to improve the estimation quality for higher order sensitivity indices. The proposed space-partition method is compared with the more traditional method and test cases show that it outperforms the traditional one

  7. A Web service substitution method based on service cluster nets

    Science.gov (United States)

    Du, YuYue; Gai, JunJing; Zhou, MengChu

    2017-11-01

    Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

  8. Random walk-based similarity measure method for patterns in complex object

    Directory of Open Access Journals (Sweden)

    Liu Shihu

    2017-04-01

    Full Text Available This paper discusses the similarity of the patterns in complex objects. The complex object is composed both of the attribute information of patterns and the relational information between patterns. Bearing in mind the specificity of complex object, a random walk-based similarity measurement method for patterns is constructed. In this method, the reachability of any two patterns with respect to the relational information is fully studied, and in the case of similarity of patterns with respect to the relational information can be calculated. On this bases, an integrated similarity measurement method is proposed, and algorithms 1 and 2 show the performed calculation procedure. One can find that this method makes full use of the attribute information and relational information. Finally, a synthetic example shows that our proposed similarity measurement method is validated.

  9. A volume of fluid method based on multidimensional advection and spline interface reconstruction

    International Nuclear Information System (INIS)

    Lopez, J.; Hernandez, J.; Gomez, P.; Faura, F.

    2004-01-01

    A new volume of fluid method for tracking two-dimensional interfaces is presented. The method involves a multidimensional advection algorithm based on the use of edge-matched flux polygons to integrate the volume fraction evolution equation, and a spline-based reconstruction algorithm. The accuracy and efficiency of the proposed method are analyzed using different tests, and the results are compared with those obtained recently by other authors. Despite its simplicity, the proposed method represents a significant improvement, and compares favorably with other volume of fluid methods as regards the accuracy and efficiency of both the advection and reconstruction steps

  10. Frequency scanning-based stability analysis method for grid-connected inverter system

    DEFF Research Database (Denmark)

    Wang, Yanbo; Wang, Xiongfei; Blaabjerg, Frede

    2017-01-01

    This paper proposes a frequency scanning-based impedance analysis for stability assessment of grid-connected inverter system, which is able to perform stability assessment without using system mathematical models and inherit the superior feature of impedance-based stability criterion with conside......This paper proposes a frequency scanning-based impedance analysis for stability assessment of grid-connected inverter system, which is able to perform stability assessment without using system mathematical models and inherit the superior feature of impedance-based stability criterion...... with consideration of the inverter nonlinearities. Small current disturbance is injected into grid-connected inverter system in a particular frequency range, and the impedance is computed according to the harmonic-frequency response using Fourier analysis, and then the stability is predicted on the basis...... of the impedance stability criterion. The stability issues of grid-connected inverters with grid-current feedback and the converter-current feedback are addressed using the proposed method. The results obtained from simulation and experiments validate the effectiveness of the method. The frequency scanning...

  11. A model-based radiography restoration method based on simple scatter-degradation scheme for improving image visibility

    Science.gov (United States)

    Kim, K.; Kang, S.; Cho, H.; Kang, W.; Seo, C.; Park, C.; Lee, D.; Lim, H.; Lee, H.; Kim, G.; Park, S.; Park, J.; Kim, W.; Jeon, D.; Woo, T.; Oh, J.

    2018-02-01

    In conventional planar radiography, image visibility is often limited mainly due to the superimposition of the object structure under investigation and the artifacts caused by scattered x-rays and noise. Several methods, including computed tomography (CT) as a multiplanar imaging modality, air-gap and grid techniques for the reduction of scatters, phase-contrast imaging as another image-contrast modality, etc., have extensively been investigated in attempt to overcome these difficulties. However, those methods typically require higher x-ray doses or special equipment. In this work, as another approach, we propose a new model-based radiography restoration method based on simple scatter-degradation scheme where the intensity of scattered x-rays and the transmission function of a given object are estimated from a single x-ray image to restore the original degraded image. We implemented the proposed algorithm and performed an experiment to demonstrate its viability. Our results indicate that the degradation of image characteristics by scattered x-rays and noise was effectively recovered by using the proposed method, which improves the image visibility in radiography considerably.

  12. Constant Jacobian Matrix-Based Stochastic Galerkin Method for Probabilistic Load Flow

    Directory of Open Access Journals (Sweden)

    Yingyun Sun

    2016-03-01

    Full Text Available An intrusive spectral method of probabilistic load flow (PLF is proposed in the paper, which can handle the uncertainties arising from renewable energy integration. Generalized polynomial chaos (gPC expansions of dependent random variables are utilized to build a spectral stochastic representation of PLF model. Instead of solving the coupled PLF model with a traditional, cumbersome method, a modified stochastic Galerkin (SG method is proposed based on the P-Q decoupling properties of load flow in power system. By introducing two pre-calculated constant sparse Jacobian matrices, the computational burden of the SG method is significantly reduced. Two cases, IEEE 14-bus and IEEE 118-bus systems, are used to verify the computation speed and efficiency of the proposed method.

  13. Maintenance planning support method for nuclear power plants based on collective decision making

    International Nuclear Information System (INIS)

    Shimizu, Shunichi; Sakurai, Shoji; Takaoka, Kazushi; Kanemoto, Shigeru; Fukutomi, Shigeki

    1992-01-01

    Inspection and maintenance planning in nuclear power plants is conducted by decision making based on experts' collective consensus. However, since a great deal of time and effort is required to reach a consensus among expert judgments, the establishment of effective decision making methods is necessary. Therefore, the authors developed a method for supporting collective decision making, based on a combination of three types of decision making methods; the Characteristic Diagram method, Interpretative Structural Modeling method, and the Analytic Hierarchy Process method. The proposed method enables us to determine the evaluation criteria systematically for collective decision making, and also allows extracting collective decisions using simplified questionnaires. The proposed method can support reaching a consensus of groups effectively through the evaluation of collective decision structural models and their characteristics. In this paper, the effectiveness of the proposed method was demonstrated through its application to the decision making problem concerning whether or not the improved ultrasonic testing equipment should be adopted at nuclear power plants. (author)

  14. Traffic Speed Data Imputation Method Based on Tensor Completion

    Directory of Open Access Journals (Sweden)

    Bin Ran

    2015-01-01

    Full Text Available Traffic speed data plays a key role in Intelligent Transportation Systems (ITS; however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS. In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC, an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

  15. Springback Compensation Based on FDM-DTF Method

    International Nuclear Information System (INIS)

    Liu Qiang; Kang Lan

    2010-01-01

    Stamping part error caused by springback is usually considered to be a tooling defect in sheet metal forming process. This problem can be corrected by adjusting the tooling shape to appropriate shape. In this paper, springback compensation based on FDM-DTF method is proposed to be used for design and modification of the tooling shape. Firstly, based on FDM method, the tooling shape is designed by reversing inner force's direction at the end of forming simulation, the required tooling shape can be got through some iterations. Secondly actual tooling is produced based on results got in the first step. When the tooling and part surface discrete data are investigated, the transfer function between numerical springback error and real springback error can be calculated based on wavelet transform results, which can be used in predicting the tooling shape for the desired product. Finally the FDM-DTF method is proved to control springback effectively after it has been applied in the 2D irregular product springback control.

  16. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

    According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

  17. Singularity Processing Method of Microstrip Line Edge Based on LOD-FDTD

    Directory of Open Access Journals (Sweden)

    Lei Li

    2014-01-01

    Full Text Available In order to improve the performance of the accuracy and efficiency for analyzing the microstrip structure, a singularity processing method is proposed theoretically and experimentally based on the fundamental locally one-dimensional finite difference time domain (LOD-FDTD with second-order temporal accuracy (denoted as FLOD2-FDTD. The proposed method can highly improve the performance of the FLOD2-FDTD even when the conductor is embedded into more than half of the cell by the coordinate transformation. The experimental results showed that the proposed method can achieve higher accuracy when the time step size is less than or equal to 5 times of that the Courant-Friedrich-Levy (CFL condition allowed. In comparison with the previously reported methods, the proposed method for calculating electromagnetic field near microstrip line edge not only improves the efficiency, but also can provide a higher accuracy.

  18. Improvement of Accuracy for Background Noise Estimation Method Based on TPE-AE

    Science.gov (United States)

    Itai, Akitoshi; Yasukawa, Hiroshi

    This paper proposes a method of a background noise estimation based on the tensor product expansion with a median and a Monte carlo simulation. We have shown that a tensor product expansion with absolute error method is effective to estimate a background noise, however, a background noise might not be estimated by using conventional method properly. In this paper, it is shown that the estimate accuracy can be improved by using proposed methods.

  19. New LSB-based colour image steganography method to enhance ...

    Indian Academy of Sciences (India)

    Mustafa Cem kasapbaşi

    2018-04-27

    Apr 27, 2018 ... evaluate the proposed method, comparative performance tests are carried out against different spatial image ... image steganography applications based on LSB are ..... worst case scenario could occur when having highest.

  20. Methodological proposal for environmental impact evaluation since different specific methods

    International Nuclear Information System (INIS)

    Leon Pelaez, Juan Diego; Lopera Arango Gabriel Jaime

    1999-01-01

    Some conceptual and practical elements related to environmental impact evaluation are described and related to the preparation of technical reports (environmental impact studies and environmental management plans) to be presented to environmental authorities for obtaining the environmental permits for development projects. In the first part of the document a summary of the main aspects of normative type is made that support the studies of environmental impact in Colombia. We propose a diagram for boarding and elaboration of the evaluation of environmental impact, which begins with the description of the project and of the environmental conditions in the area of the same. Passing then to identify the impacts through a method matricial and continuing with the quantitative evaluation of the same. For which we propose the use of the method developed by Arboleda (1994). Also we propose to qualify the activities of the project and the components of the environment in their relative importance, by means of a method here denominated agglomerate evaluation. Which allows finding those activities more impacting and the mostly impacted components. Lastly it is presented some models for the elaboration and presentation of the environmental management plans. The pursuit programs and those of environmental supervision

  1. A proposal of Fourier-Bessel expansion with optimized ensembles of bases to analyse two dimensional image

    Science.gov (United States)

    Yamasaki, K.; Fujisawa, A.; Nagashima, Y.

    2017-09-01

    It is a critical issue to find the best set of fitting function bases in mode structural analysis of two dimensional images like plasma emission profiles. The paper proposes a method to optimize a set of the bases in the case of Fourier-Bessel function series, using their orthonormal property, for more efficient and precise analysis. The method is applied on a tomography image of plasma emission obtained with the Maximum-likelihood expectation maximization method in a linear cylindrical device. The result demonstrates the excellency of the method that realizes the smaller residual error and minimum Akaike information criterion using smaller number of fitting function bases.

  2. A Least Square-Based Self-Adaptive Localization Method for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Baoguo Yu

    2016-01-01

    Full Text Available In the wireless sensor network (WSN localization methods based on Received Signal Strength Indicator (RSSI, it is usually required to determine the parameters of the radio signal propagation model before estimating the distance between the anchor node and an unknown node with reference to their communication RSSI value. And finally we use a localization algorithm to estimate the location of the unknown node. However, this localization method, though high in localization accuracy, has weaknesses such as complex working procedure and poor system versatility. Concerning these defects, a self-adaptive WSN localization method based on least square is proposed, which uses the least square criterion to estimate the parameters of radio signal propagation model, which positively reduces the computation amount in the estimation process. The experimental results show that the proposed self-adaptive localization method outputs a high processing efficiency while satisfying the high localization accuracy requirement. Conclusively, the proposed method is of definite practical value.

  3. Fast Reduction Method in Dominance-Based Information Systems

    Science.gov (United States)

    Li, Yan; Zhou, Qinghua; Wen, Yongchuan

    2018-01-01

    In real world applications, there are often some data with continuous values or preference-ordered values. Rough sets based on dominance relations can effectively deal with these kinds of data. Attribute reduction can be done in the framework of dominance-relation based approach to better extract decision rules. However, the computational cost of the dominance classes greatly affects the efficiency of attribute reduction and rule extraction. This paper presents an efficient method of computing dominance classes, and further compares it with traditional method with increasing attributes and samples. Experiments on UCI data sets show that the proposed algorithm obviously improves the efficiency of the traditional method, especially for large-scale data.

  4. A Novel Bearing Fault Diagnosis Method Based on Gaussian Restricted Boltzmann Machine

    Directory of Open Access Journals (Sweden)

    Xiao-hui He

    2016-01-01

    Full Text Available To realize the fault diagnosis of bearing effectively, this paper presents a novel bearing fault diagnosis method based on Gaussian restricted Boltzmann machine (Gaussian RBM. Vibration signals are firstly resampled to the same equivalent speed. Subsequently, the envelope spectrums of the resampled data are used directly as the feature vectors to represent the fault types of bearing. Finally, in order to deal with the high-dimensional feature vectors based on envelope spectrum, a classifier model based on Gaussian RBM is applied. Gaussian RBM has the ability to provide a closed-form representation of the distribution underlying the training data, and it is very convenient for modeling high-dimensional real-valued data. Experiments on 10 different data sets verify the performance of the proposed method. The superiority of Gaussian RBM classifier is also confirmed by comparing with other classifiers, such as extreme learning machine, support vector machine, and deep belief network. The robustness of the proposed method is also studied in this paper. It can be concluded that the proposed method can realize the bearing fault diagnosis accurately and effectively.

  5. Energy-Based Acoustic Source Localization Methods: A Survey

    Directory of Open Access Journals (Sweden)

    Wei Meng

    2017-02-01

    Full Text Available Energy-based source localization is an important problem in wireless sensor networks (WSNs, which has been studied actively in the literature. Numerous localization algorithms, e.g., maximum likelihood estimation (MLE and nonlinear-least-squares (NLS methods, have been reported. In the literature, there are relevant review papers for localization in WSNs, e.g., for distance-based localization. However, not much work related to energy-based source localization is covered in the existing review papers. Energy-based methods are proposed and specially designed for a WSN due to its limited sensor capabilities. This paper aims to give a comprehensive review of these different algorithms for energy-based single and multiple source localization problems, their merits and demerits and to point out possible future research directions.

  6. A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation

    Directory of Open Access Journals (Sweden)

    Tianshuang Qiu

    2007-12-01

    Full Text Available This paper proposes a geometric method to locate a mobile station (MS in a mobile cellular network when both the range and angle measurements are corrupted by non-line-of-sight (NLOS errors. The MS location is restricted to an enclosed region by geometric constraints from the temporal-spatial characteristics of the radio propagation channel. A closed-form equation of the MS position, time of arrival (TOA, angle of arrival (AOA, and angle spread is provided. The solution space of the equation is very large because the angle spreads are random variables in nature. A constrained objective function is constructed to further limit the MS position. A Lagrange multiplier-based solution and a numerical solution are proposed to resolve the MS position. The estimation quality of the estimator in term of “biased” or “unbiased” is discussed. The scale factors, which may be used to evaluate NLOS propagation level, can be estimated by the proposed method. AOA seen at base stations may be corrected to some degree. The performance comparisons among the proposed method and other hybrid location methods are investigated on different NLOS error models and with two scenarios of cell layout. It is found that the proposed method can deal with NLOS error effectively, and it is attractive for location estimation in cellular networks.

  7. A QFD-based optimization method for a scalable product platform

    Science.gov (United States)

    Luo, Xinggang; Tang, Jiafu; Kwong, C. K.

    2010-02-01

    In order to incorporate the customer into the early phase of the product development cycle and to better satisfy customers' requirements, this article adopts quality function deployment (QFD) for optimal design of a scalable product platform. A five-step QFD-based method is proposed to determine the optimal values for platform engineering characteristics (ECs) and non-platform ECs of the products within a product family. First of all, the houses of quality (HoQs) for all product variants are developed and a QFD-based optimization approach is used to determine the optimal ECs for each product variant. Sensitivity analysis is performed for each EC with respect to overall customer satisfaction (OCS). Based on the obtained sensitivity indices of ECs, a mathematical model is established to simultaneously optimize the values of the platform and the non-platform ECs. Finally, by comparing and analysing the optimal solutions with different number of platform ECs, the ECs with which the worst OCS loss can be avoided are selected as platform ECs. An illustrative example is used to demonstrate the feasibility of this method. A comparison between the proposed method and a two-step approach is conducted on the example. The comparison shows that, as a kind of single-stage approach, the proposed method yields better average degree of customer satisfaction due to the simultaneous optimization of platform and non-platform ECs.

  8. Support vector machine-based facial-expression recognition method combining shape and appearance

    Science.gov (United States)

    Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

    2010-11-01

    Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

  9. An Efficient Graph-based Method for Long-term Land-use Change Statistics

    Directory of Open Access Journals (Sweden)

    Yipeng Zhang

    2015-12-01

    Full Text Available Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.

  10. A novel scene-based non-uniformity correction method for SWIR push-broom hyperspectral sensors

    Science.gov (United States)

    Hu, Bin-Lin; Hao, Shi-Jing; Sun, De-Xin; Liu, Yin-Nian

    2017-09-01

    A novel scene-based non-uniformity correction (NUC) method for short-wavelength infrared (SWIR) push-broom hyperspectral sensors is proposed and evaluated. This method relies on the assumption that for each band there will be ground objects with similar reflectance to form uniform regions when a sufficient number of scanning lines are acquired. The uniform regions are extracted automatically through a sorting algorithm, and are used to compute the corresponding NUC coefficients. SWIR hyperspectral data from airborne experiment are used to verify and evaluate the proposed method, and results show that stripes in the scenes have been well corrected without any significant information loss, and the non-uniformity is less than 0.5%. In addition, the proposed method is compared to two other regular methods, and they are evaluated based on their adaptability to the various scenes, non-uniformity, roughness and spectral fidelity. It turns out that the proposed method shows strong adaptability, high accuracy and efficiency.

  11. An Improved Interferometric Calibration Method Based on Independent Parameter Decomposition

    Science.gov (United States)

    Fan, J.; Zuo, X.; Li, T.; Chen, Q.; Geng, X.

    2018-04-01

    Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM). The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs). However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD). Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

  12. An Optimization Method for Condition Based Maintenance of Aircraft Fleet Considering Prognostics Uncertainty

    Directory of Open Access Journals (Sweden)

    Qiang Feng

    2014-01-01

    Full Text Available An optimization method for condition based maintenance (CBM of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL distribution of the key line replaceable Module (LRM has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.

  13. Proposal for a Method for Business Model Performance Assessment: Toward an Experimentation Tool for Business Model Innovation

    Directory of Open Access Journals (Sweden)

    Antonio Batocchio

    2017-04-01

    Full Text Available The representation of business models has been recently widespread, especially in the pursuit of innovation. However, defining a company’s business model is sometimes limited to discussion and debates. This study observes the need for performance measurement so that business models can be data-driven. To meet this goal, the work proposed as a hypothesis the creation of a method that combines the practices of the Balanced Scorecard with a method of business models representation – the Business Model Canvas. Such a combination was based on study of conceptual adaptation, resulting in an application roadmap. A case study application was performed to check the functionality of the proposition, focusing on startup organizations. It was concluded that based on the performance assessment of the business model it is possible to propose the search for change through experimentation, a path that can lead to business model innovation.

  14. Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Kang Xie

    2015-01-01

    Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

  15. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hu-Chen [School of Management, Hefei University of Technology, Hefei 230009 (China); Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552 (Japan); Wu, Jing [Department of Public Management, Tongji University, Shanghai 200092 (China); Li, Ping, E-mail: yiwuchulp@126.com [Shanghai Pudong New Area Zhoupu Hospital, No. 135 Guanyue Road, Shanghai 201318 (China); East Hospital Affiliated to Tongji University, No. 150 Jimo Road, Shanghai 200120 (China)

    2013-12-15

    Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.

  16. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

    International Nuclear Information System (INIS)

    Liu, Hu-Chen; Wu, Jing; Li, Ping

    2013-01-01

    Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way

  17. Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

    Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

  18. A method based on moving least squares for XRII image distortion correction

    International Nuclear Information System (INIS)

    Yan Shiju; Wang Chengtao; Ye Ming

    2007-01-01

    This paper presents a novel integrated method to correct geometric distortions of XRII (x-ray image intensifier) images. The method has been compared, in terms of mean-squared residual error measured at control and intermediate points, with two traditional local methods and a traditional global methods. The proposed method is based on the methods of moving least squares (MLS) and polynomial fitting. Extensive experiments were performed on simulated and real XRII images. In simulation, the effect of pincushion distortion, sigmoidal distortion, local distortion, noise, and the number of control points was tested. The traditional local methods were sensitive to pincushion and sigmoidal distortion. The traditional global method was only sensitive to sigmoidal distortion. The proposed method was found neither sensitive to pincushion distortion nor sensitive to sigmoidal distortion. The sensitivity of the proposed method to local distortion was lower than or comparable with that of the traditional global method. The sensitivity of the proposed method to noise was higher than that of all three traditional methods. Nevertheless, provided the standard deviation of noise was not greater than 0.1 pixels, accuracy of the proposed method is still higher than the traditional methods. The sensitivity of the proposed method to the number of control points was greatly lower than that of the traditional methods. Provided that a proper cutoff radius is chosen, accuracy of the proposed method is higher than that of the traditional methods. Experiments on real images, carried out by using a 9 in. XRII, showed that residual error of the proposed method (0.2544±0.2479 pixels) is lower than that of the traditional global method (0.4223±0.3879 pixels) and local methods (0.4555±0.3518 pixels and 0.3696±0.4019 pixels, respectively)

  19. Acoustic Source Localization via Subspace Based Method Using Small Aperture MEMS Arrays

    Directory of Open Access Journals (Sweden)

    Xin Zhang

    2014-01-01

    Full Text Available Small aperture microphone arrays provide many advantages for portable devices and hearing aid equipment. In this paper, a subspace based localization method is proposed for acoustic source using small aperture arrays. The effects of array aperture on localization are analyzed by using array response (array manifold. Besides array aperture, the frequency of acoustic source and the variance of signal power are simulated to demonstrate how to optimize localization performance, which is carried out by introducing frequency error with the proposed method. The proposed method for 5 mm array aperture is validated by simulations and experiments with MEMS microphone arrays. Different types of acoustic sources can be localized with the highest precision of 6 degrees even in the presence of wind noise and other noises. Furthermore, the proposed method reduces the computational complexity compared with other methods.

  20. A Proposal on the Quantitative Homogeneity Analysis Method of SEM Images for Material Inspections

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Kim, Jong Woo; Shin, Chang Ho [Hanyang University, Seoul (Korea, Republic of); Choi, Jung-Hoon; Cho, In-Hak; Park, Hwan Seo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-05-15

    A scanning electron microscope (SEM) is a method to inspect the surface microstructure of materials. The SEM uses electron beams for imaging high magnifications of material surfaces; therefore, various chemical analyses can be performed from the SEM images. Therefore, it is widely used for the material inspection, chemical characteristic analysis, and biological analysis. For the nuclear criticality analysis field, it is an important parameter to check the homogeneity of the compound material for using it in the nuclear system. In our previous study, the SEM was tried to use for the homogeneity analysis of the materials. In this study, a quantitative homogeneity analysis method of SEM images is proposed for the material inspections. The method is based on the stochastic analysis method with the information of the grayscales of the SEM images.

  1. A Proposal on the Quantitative Homogeneity Analysis Method of SEM Images for Material Inspections

    International Nuclear Information System (INIS)

    Kim, Song Hyun; Kim, Jong Woo; Shin, Chang Ho; Choi, Jung-Hoon; Cho, In-Hak; Park, Hwan Seo

    2015-01-01

    A scanning electron microscope (SEM) is a method to inspect the surface microstructure of materials. The SEM uses electron beams for imaging high magnifications of material surfaces; therefore, various chemical analyses can be performed from the SEM images. Therefore, it is widely used for the material inspection, chemical characteristic analysis, and biological analysis. For the nuclear criticality analysis field, it is an important parameter to check the homogeneity of the compound material for using it in the nuclear system. In our previous study, the SEM was tried to use for the homogeneity analysis of the materials. In this study, a quantitative homogeneity analysis method of SEM images is proposed for the material inspections. The method is based on the stochastic analysis method with the information of the grayscales of the SEM images

  2. Convex-based void filling method for CAD-based Monte Carlo geometry modeling

    International Nuclear Information System (INIS)

    Yu, Shengpeng; Cheng, Mengyun; Song, Jing; Long, Pengcheng; Hu, Liqin

    2015-01-01

    Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time

  3. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

    Directory of Open Access Journals (Sweden)

    Ge Jianjun

    2017-12-01

    Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

  4. Finger-vein and fingerprint recognition based on a feature-level fusion method

    Science.gov (United States)

    Yang, Jinfeng; Hong, Bofeng

    2013-07-01

    Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

  5. An atlas-based multimodal registration method for 2D images with discrepancy structures.

    Science.gov (United States)

    Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

    2018-06-04

    An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

  6. A Rapid Aeroelasticity Optimization Method Based on the Stiffness characteristics

    OpenAIRE

    Yuan, Zhe; Huo, Shihui; Ren, Jianting

    2018-01-01

    A rapid aeroelasticity optimization method based on the stiffness characteristics was proposed in the present study. Large time expense in static aeroelasticity analysis based on traditional time domain aeroelasticity method is solved. Elastic axis location and torsional stiffness are discussed firstly. Both torsional stiffness and the distance between stiffness center and aerodynamic center have a direct impact on divergent velocity. The divergent velocity can be adjusted by changing the cor...

  7. Primal Decomposition-Based Method for Weighted Sum-Rate Maximization in Downlink OFDMA Systems

    Directory of Open Access Journals (Sweden)

    Weeraddana Chathuranga

    2010-01-01

    Full Text Available We consider the weighted sum-rate maximization problem in downlink Orthogonal Frequency Division Multiple Access (OFDMA systems. Motivated by the increasing popularity of OFDMA in future wireless technologies, a low complexity suboptimal resource allocation algorithm is obtained for joint optimization of multiuser subcarrier assignment and power allocation. The algorithm is based on an approximated primal decomposition-based method, which is inspired from exact primal decomposition techniques. The original nonconvex optimization problem is divided into two subproblems which can be solved independently. Numerical results are provided to compare the performance of the proposed algorithm to Lagrange relaxation based suboptimal methods as well as to optimal exhaustive search-based method. Despite its reduced computational complexity, the proposed algorithm provides close-to-optimal performance.

  8. Spectrum estimation method based on marginal spectrum

    International Nuclear Information System (INIS)

    Cai Jianhua; Hu Weiwen; Wang Xianchun

    2011-01-01

    FFT method can not meet the basic requirements of power spectrum for non-stationary signal and short signal. A new spectrum estimation method based on marginal spectrum from Hilbert-Huang transform (HHT) was proposed. The procession of obtaining marginal spectrum in HHT method was given and the linear property of marginal spectrum was demonstrated. Compared with the FFT method, the physical meaning and the frequency resolution of marginal spectrum were further analyzed. Then the Hilbert spectrum estimation algorithm was discussed in detail, and the simulation results were given at last. The theory and simulation shows that under the condition of short data signal and non-stationary signal, the frequency resolution and estimation precision of HHT method is better than that of FFT method. (authors)

  9. Proposed frustrated-total-reflection acoustic sensing method

    International Nuclear Information System (INIS)

    Hull, J.R.

    1981-01-01

    Modulation of electromagnetic energy transmission through a frustrated-total-reflection device by pressure-induced changes in the index of refraction is proposed for use as an acoustic detector. Maximum sensitivity occurs for angles of incidence near the critical angle. The minimum detectable pressure in air is limited by Brownian noise. Acoustic propagation losses and diffraction of the optical beam by the acoustic signal limit the minimum acoustic wavelength to lengths of the order of the spatial extent of the optical beam. The response time of the method is fast enough to follow individual acoustic waves

  10. A FPGA-based identity authority method in quantum key distribution system

    International Nuclear Information System (INIS)

    Cui Ke; Luo Chunli; Zhang Hongfei; Lin Shengzhao; Jin Ge; Wang Jian

    2012-01-01

    In this article, an identity authority method realized in hardware is developed which is used in quantum key distribution (QKD) systems. This method is based on LFSR-Teoplitz hashing matrix. Its benefits relay on its easy implementation in hardware and high secure coefficient. It can gain very high security by means of splitting part of the final key generated from QKD systems as the seed where it is required in the identity authority method. We propose an specific flow of the identity authority method according to the problems and features of the hardware. The proposed method can satisfy many kinds of QKD systems. (authors)

  11. Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

    KAUST Repository

    Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem

    2016-01-01

    In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear

  12. [A novel method based on Y-shaped cotton-polyester thread microfluidic channel].

    Science.gov (United States)

    Wang, Lu; Shi, Yan-ru; Yan, Hong-tao

    2014-08-01

    A novel method based on Y-shaped microfluidic channel was firstly proposed in this study. The microfluidic channel was made of two cotton-polyester threads based on the capillary effect of cotton-polyester threads for the determination solutions. A special device was developed to fix the Y-shaped microfluidic channel by ourselves, through which the length and the tilt angle of the channel can be adjusted as requested. The spectrophotometry was compared with Scan-Adobe Photoshop software processing method. The former had a lower detection limit while the latter showed advantages in both convenience and fast operations and lower amount of samples. The proposed method was applied to the determination of nitrite. The linear ranges and detection limits are 1.0-70 micromol x L(-1), 0.66 micromol x L(-1) (spectrophotometry) and 50-450 micromol x L(-1), 45.10 micromol x L(-1) (Scan-Adobe Photoshop software processing method) respectively. This method has been successfully used to the determination of nitrite in soil samples and moat water with recoveries between 96.7% and 104%. It was proved that the proposed method was a low-cost, rapid and convenient analytical method with extensive application prospect.

  13. Object-Based Dense Matching Method for Maintaining Structure Characteristics of Linear Buildings.

    Science.gov (United States)

    Su, Nan; Yan, Yiming; Qiu, Mingjie; Zhao, Chunhui; Wang, Liguo

    2018-03-29

    In this paper, we proposed a novel object-based dense matching method specially for the high-precision disparity map of building objects in urban areas, which can maintain accurate object structure characteristics. The proposed framework mainly includes three stages. Firstly, an improved edge line extraction method is proposed for the edge segments to fit closely to building outlines. Secondly, a fusion method is proposed for the outlines under the constraint of straight lines, which can maintain the building structural attribute with parallel or vertical edges, which is very useful for the dense matching method. Finally, we proposed an edge constraint and outline compensation (ECAOC) dense matching method to maintain building object structural characteristics in the disparity map. In the proposed method, the improved edge lines are used to optimize matching search scope and matching template window, and the high-precision building outlines are used to compensate the shape feature of building objects. Our method can greatly increase the matching accuracy of building objects in urban areas, especially at building edges. For the outline extraction experiments, our fusion method verifies the superiority and robustness on panchromatic images of different satellites and different resolutions. For the dense matching experiments, our ECOAC method shows great advantages for matching accuracy of building objects in urban areas compared with three other methods.

  14. Object-Based Dense Matching Method for Maintaining Structure Characteristics of Linear Buildings

    Directory of Open Access Journals (Sweden)

    Nan Su

    2018-03-01

    Full Text Available In this paper, we proposed a novel object-based dense matching method specially for the high-precision disparity map of building objects in urban areas, which can maintain accurate object structure characteristics. The proposed framework mainly includes three stages. Firstly, an improved edge line extraction method is proposed for the edge segments to fit closely to building outlines. Secondly, a fusion method is proposed for the outlines under the constraint of straight lines, which can maintain the building structural attribute with parallel or vertical edges, which is very useful for the dense matching method. Finally, we proposed an edge constraint and outline compensation (ECAOC dense matching method to maintain building object structural characteristics in the disparity map. In the proposed method, the improved edge lines are used to optimize matching search scope and matching template window, and the high-precision building outlines are used to compensate the shape feature of building objects. Our method can greatly increase the matching accuracy of building objects in urban areas, especially at building edges. For the outline extraction experiments, our fusion method verifies the superiority and robustness on panchromatic images of different satellites and different resolutions. For the dense matching experiments, our ECOAC method shows great advantages for matching accuracy of building objects in urban areas compared with three other methods.

  15. A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum

    Directory of Open Access Journals (Sweden)

    Pan Liu

    2017-05-01

    Full Text Available This paper presents a wavelet-based Gaussian method (WGM for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF. The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

  16. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

    Science.gov (United States)

    Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

    2017-02-20

    In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  17. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

    Directory of Open Access Journals (Sweden)

    Anbang Zhao

    2017-02-01

    Full Text Available In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  18. Edge detection methods based on generalized type-2 fuzzy logic

    CERN Document Server

    Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

    2017-01-01

    In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

  19. Node-based finite element method for large-scale adaptive fluid analysis in parallel environments

    International Nuclear Information System (INIS)

    Toshimitsu, Fujisawa; Genki, Yagawa

    2003-01-01

    In this paper, a FEM-based (finite element method) mesh free method with a probabilistic node generation technique is presented. In the proposed method, all computational procedures, from the mesh generation to the solution of a system of equations, can be performed fluently in parallel in terms of nodes. Local finite element mesh is generated robustly around each node, even for harsh boundary shapes such as cracks. The algorithm and the data structure of finite element calculation are based on nodes, and parallel computing is realized by dividing a system of equations by the row of the global coefficient matrix. In addition, the node-based finite element method is accompanied by a probabilistic node generation technique, which generates good-natured points for nodes of finite element mesh. Furthermore, the probabilistic node generation technique can be performed in parallel environments. As a numerical example of the proposed method, we perform a compressible flow simulation containing strong shocks. Numerical simulations with frequent mesh refinement, which are required for such kind of analysis, can effectively be performed on parallel processors by using the proposed method. (authors)

  20. Node-based finite element method for large-scale adaptive fluid analysis in parallel environments

    Energy Technology Data Exchange (ETDEWEB)

    Toshimitsu, Fujisawa [Tokyo Univ., Collaborative Research Center of Frontier Simulation Software for Industrial Science, Institute of Industrial Science (Japan); Genki, Yagawa [Tokyo Univ., Department of Quantum Engineering and Systems Science (Japan)

    2003-07-01

    In this paper, a FEM-based (finite element method) mesh free method with a probabilistic node generation technique is presented. In the proposed method, all computational procedures, from the mesh generation to the solution of a system of equations, can be performed fluently in parallel in terms of nodes. Local finite element mesh is generated robustly around each node, even for harsh boundary shapes such as cracks. The algorithm and the data structure of finite element calculation are based on nodes, and parallel computing is realized by dividing a system of equations by the row of the global coefficient matrix. In addition, the node-based finite element method is accompanied by a probabilistic node generation technique, which generates good-natured points for nodes of finite element mesh. Furthermore, the probabilistic node generation technique can be performed in parallel environments. As a numerical example of the proposed method, we perform a compressible flow simulation containing strong shocks. Numerical simulations with frequent mesh refinement, which are required for such kind of analysis, can effectively be performed on parallel processors by using the proposed method. (authors)

  1. An effective trust-based recommendation method using a novel graph clustering algorithm

    Science.gov (United States)

    Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

    2015-10-01

    Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

  2. Emitter signal separation method based on multi-level digital channelization

    Science.gov (United States)

    Han, Xun; Ping, Yifan; Wang, Sujun; Feng, Ying; Kuang, Yin; Yang, Xinquan

    2018-02-01

    To solve the problem of emitter separation under complex electromagnetic environment, a signal separation method based on multi-level digital channelization is proposed in this paper. A two-level structure which can divide signal into different channel is designed first, after that, the peaks of different channels are tracked using the track filter and the coincident signals in time domain are separated in time-frequency domain. Finally, the time domain waveforms of different signals are acquired by reverse transformation. The validness of the proposed method is proved by experiment.

  3. AN IMPROVED INTERFEROMETRIC CALIBRATION METHOD BASED ON INDEPENDENT PARAMETER DECOMPOSITION

    Directory of Open Access Journals (Sweden)

    J. Fan

    2018-04-01

    Full Text Available Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM. The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs. However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD. Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

  4. A new method of machine vision reprocessing based on cellular neural networks

    International Nuclear Information System (INIS)

    Jianhua, W.; Liping, Z.; Fenfang, Z.; Guojian, H.

    1996-01-01

    This paper proposed a method of image preprocessing in machine vision based on Cellular Neural Network (CNN). CNN is introduced to design image smoothing, image recovering, image boundary detecting and other image preprocessing problems. The proposed methods are so simple that the speed of algorithms are increased greatly to suit the needs of real-time image processing. The experimental results show a satisfactory reply

  5. A digital image-based method for determining of total acidity in red wines using acid-base titration without indicator.

    Science.gov (United States)

    Tôrres, Adamastor Rodrigues; Lyra, Wellington da Silva; de Andrade, Stéfani Iury Evangelista; Andrade, Renato Allan Navarro; da Silva, Edvan Cirino; Araújo, Mário César Ugulino; Gaião, Edvaldo da Nóbrega

    2011-05-15

    This work proposes the use of digital image-based method for determination of total acidity in red wines by means of acid-base titration without using an external indicator or any pre-treatment of the sample. Digital images present the colour of the emergent radiation which is complementary to the radiation absorbed by anthocyanines present in wines. Anthocyanines change colour depending on the pH of the medium, and from the variation of colour in the images obtained during titration, the end point can be localized with accuracy and precision. RGB-based values were employed to build titration curves, and end points were localized by second derivative curves. The official method recommends potentiometric titration with a NaOH standard solution, and sample dilution until the pH reaches 8.2-8.4. In order to illustrate the feasibility of the proposed method, titrations of ten red wines were carried out. Results were compared with the reference method, and no statistically significant difference was observed between the results by applying the paired t-test at the 95% confidence level. The proposed method yielded more precise results than the official method. This is due to the trivariate nature of the measurements (RGB), associated with digital images. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. VOLUMETRIC METHOD FOR EVALUATION OF BEACHES VARIABILITY BASED ON GIS-TOOLS

    Directory of Open Access Journals (Sweden)

    V. V. Dolotov

    2015-01-01

    Full Text Available In frame of cadastral beach evaluation the volumetric method of natural variability index is proposed. It base on spatial calculations with Cut-Fill method and volume accounting ofboththe common beach contour and specific areas for the each time.

  7. A GPS-Based Control Method for Load Sharing and Power Quality Improvement in Microgrids

    DEFF Research Database (Denmark)

    Golsorkhi, Mohammad; Lu, Dylan; Savaghebi, Mehdi

    2016-01-01

    This paper proposes a novel control method for accurate sharing of load current among the Distributed Energy Resources (DER) and high power quality operating in islanded ac microgrids. This control scheme is based on hierarchical structure comprising of decentralized primary controllers and a cen....... The secondary controller produces compensation signals at fundamental and dominant harmonics to improve the voltage quality at a sensitive load bus. Experimental results are presented to validate the efficacy of the proposed method.......This paper proposes a novel control method for accurate sharing of load current among the Distributed Energy Resources (DER) and high power quality operating in islanded ac microgrids. This control scheme is based on hierarchical structure comprising of decentralized primary controllers...

  8. A Rapid Coordinate Transformation Method Applied in Industrial Robot Calibration Based on Characteristic Line Coincidence

    Directory of Open Access Journals (Sweden)

    Bailing Liu

    2016-02-01

    Full Text Available Coordinate transformation plays an indispensable role in industrial measurements, including photogrammetry, geodesy, laser 3-D measurement and robotics. The widely applied methods of coordinate transformation are generally based on solving the equations of point clouds. Despite the high accuracy, this might result in no solution due to the use of ill conditioned matrices. In this paper, a novel coordinate transformation method is proposed, not based on the equation solution but based on the geometric transformation. We construct characteristic lines to represent the coordinate systems. According to the space geometry relation, the characteristic line scan is made to coincide by a series of rotations and translations. The transformation matrix can be obtained using matrix transformation theory. Experiments are designed to compare the proposed method with other methods. The results show that the proposed method has the same high accuracy, but the operation is more convenient and flexible. A multi-sensor combined measurement system is also presented to improve the position accuracy of a robot with the calibration of the robot kinematic parameters. Experimental verification shows that the position accuracy of robot manipulator is improved by 45.8% with the proposed method and robot calibration.

  9. A Rapid Coordinate Transformation Method Applied in Industrial Robot Calibration Based on Characteristic Line Coincidence

    Science.gov (United States)

    Liu, Bailing; Zhang, Fumin; Qu, Xinghua; Shi, Xiaojia

    2016-01-01

    Coordinate transformation plays an indispensable role in industrial measurements, including photogrammetry, geodesy, laser 3-D measurement and robotics. The widely applied methods of coordinate transformation are generally based on solving the equations of point clouds. Despite the high accuracy, this might result in no solution due to the use of ill conditioned matrices. In this paper, a novel coordinate transformation method is proposed, not based on the equation solution but based on the geometric transformation. We construct characteristic lines to represent the coordinate systems. According to the space geometry relation, the characteristic line scan is made to coincide by a series of rotations and translations. The transformation matrix can be obtained using matrix transformation theory. Experiments are designed to compare the proposed method with other methods. The results show that the proposed method has the same high accuracy, but the operation is more convenient and flexible. A multi-sensor combined measurement system is also presented to improve the position accuracy of a robot with the calibration of the robot kinematic parameters. Experimental verification shows that the position accuracy of robot manipulator is improved by 45.8% with the proposed method and robot calibration. PMID:26901203

  10. Combining the Pixel-based and Object-based Methods for Building Change Detection Using High-resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    ZHANG Zhiqiang

    2018-01-01

    Full Text Available Timely and accurate change detection of buildings provides important information for urban planning and management.Accompanying with the rapid development of satellite remote sensing technology,detecting building changes from high-resolution remote sensing images have received wide attention.Given that pixel-based methods of change detection often lead to low accuracy while object-based methods are complicated for uses,this research proposes a method that combines pixel-based and object-based methods for detecting building changes from high-resolution remote sensing images.First,based on the multiple features extracted from the high-resolution images,a random forest classifier is applied to detect changed building at the pixel level.Then,a segmentation method is applied to segement the post-phase remote sensing image and to get post-phase image objects.Finally,both changed building at the pixel level and post-phase image objects are fused to recognize the changed building objects.Multi-temporal QuickBird images are used as experiment data for building change detection with high-resolution remote sensing images,the results indicate that the proposed method could reduce the influence of environmental difference,such as light intensity and view angle,on building change detection,and effectively improve the accuracies of building change detection.

  11. Proposing Some New Ecliptics in New Testament Studies Enabled by Digital Humanities-Based Methods

    Directory of Open Access Journals (Sweden)

    James Libby

    2016-04-01

    Full Text Available “Fragmentation” is a well-worn watchword in contemporary biblical studies. But is endless fragmentation across the traditional domains of epistemology, methodology and hermeneutics the inevitable future for the postmodern exercise of biblical scholarship? In our view, multiple factors mitigate against such a future, but two command our attention here. First, digital humanities itself, through its principled use of corpora, databases and computer-based methods, seems to be remarkably capable of producing findings with high levels of face validity (interpretive agreement across multiple hermeneutical perspectives and communities. Second, and perhaps more subversively, there is a substantial body of practitioners that, per Kearney, actively question postmodernity’s impress as the final port of call for philosophy. For these practitioners deconstruction has become both indispensable — by delegitimizing hegemonies — but, in its own way, metanarratival by stultifying all other iterative, dialectical and critical processes that have historically motivated scholarship. Sensing this impasse, Kearney (1987, pp. 43-45 proposes a reimagining that is not only critical but that also embraces ποίησις, the possibility of optimistic, creative work. Such a stance within digital humanities would affirm that poietic events emerge not only through frictions and fragmentation (e.g. Kinder and McPherson 2014, pp. xiii-xviii but also through commonalties and convergence. Our approach here will be to demonstrate such a reimagining, rather than to argue for it, using two worked examples in the Greek New Testament (GNT. Those examples – digital humanities-enabled papyrology and digital humanities-enabled statistical linguistics – demonstrate ways in which the data of the text itself can be used to interrogate our perspectives and suggest that our perspectives must remain ever open to such inquiries. We conclude with a call for digital humanities to

  12. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

    Directory of Open Access Journals (Sweden)

    Chen Lu

    Full Text Available Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for

  13. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

    Science.gov (United States)

    Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

    2016-01-01

    Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

  14. A fast button surface defects detection method based on convolutional neural network

    Science.gov (United States)

    Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

    2018-01-01

    Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

  15. A fast point-cloud computing method based on spatial symmetry of Fresnel field

    Science.gov (United States)

    Wang, Xiangxiang; Zhang, Kai; Shen, Chuan; Zhu, Wenliang; Wei, Sui

    2017-10-01

    Aiming at the great challenge for Computer Generated Hologram (CGH) duo to the production of high spatial-bandwidth product (SBP) is required in the real-time holographic video display systems. The paper is based on point-cloud method and it takes advantage of the propagating reversibility of Fresnel diffraction in the propagating direction and the fringe pattern of a point source, known as Gabor zone plate has spatial symmetry, so it can be used as a basis for fast calculation of diffraction field in CGH. A fast Fresnel CGH method based on the novel look-up table (N-LUT) method is proposed, the principle fringe patterns (PFPs) at the virtual plane is pre-calculated by the acceleration algorithm and be stored. Secondly, the Fresnel diffraction fringe pattern at dummy plane can be obtained. Finally, the Fresnel propagation from dummy plan to hologram plane. The simulation experiments and optical experiments based on Liquid Crystal On Silicon (LCOS) is setup to demonstrate the validity of the proposed method under the premise of ensuring the quality of 3D reconstruction the method proposed in the paper can be applied to shorten the computational time and improve computational efficiency.

  16. Study on UPF Harmonic Current Detection Method Based on DSP

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, H J [Northwestern Polytechnical University, Xi' an 710072 (China); Pang, Y F [Xi' an University of Technology, Xi' an 710048 (China); Qiu, Z M [Xi' an University of Technology, Xi' an 710048 (China); Chen, M [Northwestern Polytechnical University, Xi' an 710072 (China)

    2006-10-15

    Unity power factor (UPF) harmonic current detection method applied to active power filter (APF) is presented in this paper. The intention of this method is to make nonlinear loads and active power filter in parallel to be an equivalent resistance. So after compensation, source current is sinusoidal, and has the same shape of source voltage. Meanwhile, there is no harmonic in source current, and the power factor becomes one. The mathematic model of proposed method and the optimum project for equivalent low pass filter in measurement are presented. Finally, the proposed detection method applied to a shunt active power filter experimental prototype based on DSP TMS320F2812 is developed. Simulation and experiment results indicate the method is simple and easy to implement, and can obtain the real-time calculation of harmonic current exactly.

  17. A novel method to design S-box based on chaotic map and genetic algorithm

    International Nuclear Information System (INIS)

    Wang, Yong; Wong, Kwok-Wo; Li, Changbing; Li, Yang

    2012-01-01

    The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.

  18. A novel method to design S-box based on chaotic map and genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yong, E-mail: wangyong_cqupt@163.com [State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044 (China); Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Wong, Kwok-Wo [Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong (Hong Kong); Li, Changbing [Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Li, Yang [Department of Automatic Control and Systems Engineering, The University of Sheffield, Mapping Street, S1 3DJ (United Kingdom)

    2012-01-30

    The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.

  19. Improved Cole parameter extraction based on the least absolute deviation method

    International Nuclear Information System (INIS)

    Yang, Yuxiang; Ni, Wenwen; Sun, Qiang; Wen, He; Teng, Zhaosheng

    2013-01-01

    The Cole function is widely used in bioimpedance spectroscopy (BIS) applications. Fitting the measured BIS data onto the model and then extracting the Cole parameters (R 0 , R ∞ , α and τ) is a common practice. Accurate extraction of the Cole parameters from the measured BIS data has great significance for evaluating the physiological or pathological status of biological tissue. The traditional least-squares (LS)-based curve fitting method for Cole parameter extraction is often sensitive to noise or outliers and becomes non-robust. This paper proposes an improved Cole parameter extraction based on the least absolute deviation (LAD) method. Comprehensive simulation experiments are carried out and the performances of the LAD method are compared with those of the LS method under the conditions of outliers, random noises and both disturbances. The proposed LAD method exhibits much better robustness under all circumstances, which demonstrates that the LAD method is deserving as an improved alternative to the LS method for Cole parameter extraction for its robustness to outliers and noises. (paper)

  20. An accurate and efficient reliability-based design optimization using the second order reliability method and improved stability transformation method

    Science.gov (United States)

    Meng, Zeng; Yang, Dixiong; Zhou, Huanlin; Yu, Bo

    2018-05-01

    The first order reliability method has been extensively adopted for reliability-based design optimization (RBDO), but it shows inaccuracy in calculating the failure probability with highly nonlinear performance functions. Thus, the second order reliability method is required to evaluate the reliability accurately. However, its application for RBDO is quite challenge owing to the expensive computational cost incurred by the repeated reliability evaluation and Hessian calculation of probabilistic constraints. In this article, a new improved stability transformation method is proposed to search the most probable point efficiently, and the Hessian matrix is calculated by the symmetric rank-one update. The computational capability of the proposed method is illustrated and compared to the existing RBDO approaches through three mathematical and two engineering examples. The comparison results indicate that the proposed method is very efficient and accurate, providing an alternative tool for RBDO of engineering structures.

  1. Missing value imputation in DNA microarrays based on conjugate gradient method.

    Science.gov (United States)

    Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

    2012-02-01

    Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. A novel three-stage distance-based consensus ranking method

    Science.gov (United States)

    Aghayi, Nazila; Tavana, Madjid

    2018-05-01

    In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

  3. Accelerated gradient methods for total-variation-based CT image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology

    2011-07-01

    Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)

  4. A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

    Directory of Open Access Journals (Sweden)

    Rongjie Kuang

    2014-03-01

    Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

  5. Hand-Eye LRF-Based Iterative Plane Detection Method for Autonomous Robotic Welding

    Directory of Open Access Journals (Sweden)

    Sungmin Lee

    2015-12-01

    Full Text Available This paper proposes a hand-eye LRF-based (laser range finder welding plane-detection method for autonomous robotic welding in the field of shipbuilding. The hand-eye LRF system consists of a 6 DOF manipulator and an LRF attached to the wrist of the manipulator. The welding plane is detected by the LRF with only the wrist's rotation to minimize a mechanical error caused by the manipulator's motion. A position on the plane is determined as an average position of the detected points on the plane, and a normal vector to the plane is determined by applying PCA (principal component analysis to the detected points. In this case, the accuracy of the detected plane is analysed by simulations with respect to the wrist's angle interval and the plane angle. As a result of the analysis, an iterative plane-detection method with the manipulator's alignment motion is proposed to improve the performance of plane detection. For verifying the feasibility and effectiveness of the proposed plane-detection method, experiments are carried out with a prototype of the hand-eye LRF-based system, which consists of a 1 DOF wrist's joint, an LRF system and a rotatable plane. In addition, the experimental results of the PCA-based plane detection method are compared with those of the two representative plane-detection methods, based on RANSAC (RANdom SAmple Consensus and the 3D Hough transform in both accuracy and computation time's points of view.

  6. Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

    Science.gov (United States)

    Lei, Yaguo; Liu, Zongyao; Wu, Xionghui; Li, Naipeng; Chen, Wu; Lin, Jing

    2015-08-01

    Multi-stage planetary gearboxes are widely applied in aerospace, automotive and heavy industries. Their key components, such as gears and bearings, can easily suffer from damage due to tough working environment. Health condition identification of planetary gearboxes aims to prevent accidents and save costs. This paper proposes a method based on multiclass relevance vector machine (mRVM) to identify health condition of multi-stage planetary gearboxes. In this method, a mRVM algorithm is adopted as a classifier, and two features, i.e. accumulative amplitudes of carrier orders (AACO) and energy ratio based on difference spectra (ERDS), are used as the input of the classifier to classify different health conditions of multi-stage planetary gearboxes. To test the proposed method, seven health conditions of a two-stage planetary gearbox are considered and vibration data is acquired from the planetary gearbox under different motor speeds and loading conditions. The results of three tests based on different data show that the proposed method obtains an improved identification performance and robustness compared with the existing method.

  7. Novel Verification Method for Timing Optimization Based on DPSO

    Directory of Open Access Journals (Sweden)

    Chuandong Chen

    2018-01-01

    Full Text Available Timing optimization for logic circuits is one of the key steps in logic synthesis. Extant research data are mainly proposed based on various intelligence algorithms. Hence, they are neither comparable with timing optimization data collected by the mainstream electronic design automation (EDA tool nor able to verify the superiority of intelligence algorithms to the EDA tool in terms of optimization ability. To address these shortcomings, a novel verification method is proposed in this study. First, a discrete particle swarm optimization (DPSO algorithm was applied to optimize the timing of the mixed polarity Reed-Muller (MPRM logic circuit. Second, the Design Compiler (DC algorithm was used to optimize the timing of the same MPRM logic circuit through special settings and constraints. Finally, the timing optimization results of the two algorithms were compared based on MCNC benchmark circuits. The timing optimization results obtained using DPSO are compared with those obtained from DC, and DPSO demonstrates an average reduction of 9.7% in the timing delays of critical paths for a number of MCNC benchmark circuits. The proposed verification method directly ascertains whether the intelligence algorithm has a better timing optimization ability than DC.

  8. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  9. A finite volume method for cylindrical heat conduction problems based on local analytical solution

    KAUST Repository

    Li, Wang

    2012-10-01

    A new finite volume method for cylindrical heat conduction problems based on local analytical solution is proposed in this paper with detailed derivation. The calculation results of this new method are compared with the traditional second-order finite volume method. The newly proposed method is more accurate than conventional ones, even though the discretized expression of this proposed method is slightly more complex than the second-order central finite volume method, making it cost more calculation time on the same grids. Numerical result shows that the total CPU time of the new method is significantly less than conventional methods for achieving the same level of accuracy. © 2012 Elsevier Ltd. All rights reserved.

  10. A finite volume method for cylindrical heat conduction problems based on local analytical solution

    KAUST Repository

    Li, Wang; Yu, Bo; Wang, Xinran; Wang, Peng; Sun, Shuyu

    2012-01-01

    A new finite volume method for cylindrical heat conduction problems based on local analytical solution is proposed in this paper with detailed derivation. The calculation results of this new method are compared with the traditional second-order finite volume method. The newly proposed method is more accurate than conventional ones, even though the discretized expression of this proposed method is slightly more complex than the second-order central finite volume method, making it cost more calculation time on the same grids. Numerical result shows that the total CPU time of the new method is significantly less than conventional methods for achieving the same level of accuracy. © 2012 Elsevier Ltd. All rights reserved.

  11. Dim target detection method based on salient graph fusion

    Science.gov (United States)

    Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

    2018-02-01

    Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

  12. Modulating Function-Based Method for Parameter and Source Estimation of Partial Differential Equations

    KAUST Repository

    Asiri, Sharefa M.

    2017-10-08

    Partial Differential Equations (PDEs) are commonly used to model complex systems that arise for example in biology, engineering, chemistry, and elsewhere. The parameters (or coefficients) and the source of PDE models are often unknown and are estimated from available measurements. Despite its importance, solving the estimation problem is mathematically and numerically challenging and especially when the measurements are corrupted by noise, which is often the case. Various methods have been proposed to solve estimation problems in PDEs which can be classified into optimization methods and recursive methods. The optimization methods are usually heavy computationally, especially when the number of unknowns is large. In addition, they are sensitive to the initial guess and stop condition, and they suffer from the lack of robustness to noise. Recursive methods, such as observer-based approaches, are limited by their dependence on some structural properties such as observability and identifiability which might be lost when approximating the PDE numerically. Moreover, most of these methods provide asymptotic estimates which might not be useful for control applications for example. An alternative non-asymptotic approach with less computational burden has been proposed in engineering fields based on the so-called modulating functions. In this dissertation, we propose to mathematically and numerically analyze the modulating functions based approaches. We also propose to extend these approaches to different situations. The contributions of this thesis are as follows. (i) Provide a mathematical analysis of the modulating function-based method (MFBM) which includes: its well-posedness, statistical properties, and estimation errors. (ii) Provide a numerical analysis of the MFBM through some estimation problems, and study the sensitivity of the method to the modulating functions\\' parameters. (iii) Propose an effective algorithm for selecting the method\\'s design parameters

  13. a Modeling Method of Fluttering Leaves Based on Point Cloud

    Science.gov (United States)

    Tang, J.; Wang, Y.; Zhao, Y.; Hao, W.; Ning, X.; Lv, K.; Shi, Z.; Zhao, M.

    2017-09-01

    Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.

  14. Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

    Science.gov (United States)

    Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

    2016-01-01

    Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

    Science.gov (United States)

    Niegowski, Maciej; Zivanovic, Miroslav

    2016-03-01

    We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  16. Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation

    Directory of Open Access Journals (Sweden)

    Shan Yang

    2016-01-01

    Full Text Available Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverter based distributed generation is proposed. The proposed method let the inverter based distributed generation be equivalent to Iθ bus, which makes it suitable to calculate the power flow of distribution network with a current limited inverter based distributed generation. And the low voltage ride through capability of inverter based distributed generation can be considered as well in this paper. Finally, some tests of power flow and short circuit current calculation are performed on a 33-bus distribution network. The calculated results from the proposed method in this paper are contrasted with those by the traditional method and the simulation method, whose results have verified the effectiveness of the integrated method suggested in this paper.

  17. A multi-agent based intelligent configuration method for aircraft fleet maintenance personnel

    Directory of Open Access Journals (Sweden)

    Feng Qiang

    2014-04-01

    Full Text Available A multi-agent based fleet maintenance personnel configuration method is proposed to solve the mission oriented aircraft fleet maintenance personnel configuration problem. The maintenance process of an aircraft fleet is analyzed first. In the process each aircraft contains multiple parts, and different parts are repaired by personnel with different majors and levels. The factors and their relationship involved in the process of maintenance are analyzed and discussed. Then the whole maintenance process is described as a 3-layer multi-agent system (MAS model. A communication and reasoning strategy among the agents is put forward. A fleet maintenance personnel configuration algorithm is proposed based on contract net protocol (CNP. Finally, a fleet of 10 aircraft is studied for verification purposes. A mission type with 3 waves of continuous dispatch is imaged. Compared with the traditional methods that can just provide configuration results, the proposed method can provide optimal maintenance strategies as well.

  18. Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT

    Directory of Open Access Journals (Sweden)

    Samaneh Mazaheri

    2015-01-01

    Full Text Available Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.

  19. Sliding mode control of photoelectric tracking platform based on the inverse system method

    Directory of Open Access Journals (Sweden)

    Yao Zong Chen

    2016-01-01

    Full Text Available In order to improve the photoelectric tracking platform tracking performance, an integral sliding mode control strategy based on inverse system decoupling method is proposed. The electromechanical dynamic model is established based on multi-body system theory and Newton-Euler method. The coupled multi-input multi-output (MIMO nonlinear system is transformed into two pseudo-linear single-input single-output (SISO subsystems based on the inverse system method. An integral sliding mode control scheme is designed for the decoupled pseudo-linear system. In order to eliminate system chattering phenomenon caused by traditional sign function in sliding-mode controller, the sign function is replaced by the Sigmoid function. Simulation results show that the proposed decoupling method and the control strategy can restrain the influences of internal coupling and disturbance effectively, and has better robustness and higher tracking accuracy.

  20. Proposed method for regulating major materials licensees

    International Nuclear Information System (INIS)

    1992-02-01

    The Director, Office of Nuclear Material Safety and Safeguards, US Nuclear Regulatory Commission, appointed a Materials Regulatory Review Task Force to conduct a broad-based review of the Commission's current licensing and oversight programs for fuel cycle and large materials plants. The task force, as requested, defined the components and subcomponents of an ideal regulatory evaluation system for these types of licensed plants and compared they to the components and subcomponents of the existing regulatory evaluation system. This report discusses findings from this comparison and proposed recommendations on the basis of these findings

  1. A Damage Prognosis Method of Girder Structures Based on Wavelet Neural Networks

    Directory of Open Access Journals (Sweden)

    Rumian Zhong

    2014-01-01

    Full Text Available Based on the basic theory of wavelet neural networks and finite element model updating method, a basic framework of damage prognosis method is proposed in this paper. Firstly, a damaged I-steel beam model testing is used to verify the feasibility and effectiveness of the proposed damage prognosis method. The results show that the predicted results of the damage prognosis method and the measured results are very well consistent, and the maximum error is less than 5%. Furthermore, Xinyihe Bridge in the Beijing-Shanghai Highway is selected as the engineering background, and the damage prognosis is conducted based on the data from the structural health monitoring system. The results show that the traffic volume will increase and seasonal differences will decrease in the next year and a half. The displacement has a slight increase and seasonal characters in the critical section of mid span, but the strain will increase distinctly. The analysis results indicate that the proposed method can be applied to the damage prognosis of girder bridge structures and has the potential for the bridge health monitoring and safety prognosis.

  2. Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

    Directory of Open Access Journals (Sweden)

    Qiaoning Yang

    2015-10-01

    Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.

  3. A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

    Directory of Open Access Journals (Sweden)

    O. Tsakiridis

    2016-01-01

    Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

  4. Monte Carlo based statistical power analysis for mediation models: methods and software.

    Science.gov (United States)

    Zhang, Zhiyong

    2014-12-01

    The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

  5. A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling.

    Science.gov (United States)

    Zhang, Chunxi; Lin, Tie

    2016-07-28

    In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method.

  6. Face Recognition Method Based on Fuzzy 2DPCA

    Directory of Open Access Journals (Sweden)

    Xiaodong Li

    2014-01-01

    Full Text Available 2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is proposed in this paper, namely, the fuzzy 2DPCA (F2DPCA. In this method, applying fuzzy K-nearest neighbor (FKNN, the membership degree matrix of the training samples is calculated, which is used to get the fuzzy means of each class. The average of fuzzy means is then incorporated into the definition of the general scatter matrix with anticipation that it can improve classification result. The comprehensive experiments on the ORL, the YALE, and the FERET face database show that the proposed method can improve the classification rates and reduce the sensitivity to variations between face images caused by changes in illumination, face expression, and face pose.

  7. Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

    Science.gov (United States)

    Jain, Ram B

    2016-08-01

    Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

  8. Dynamic Frames Based Verification Method for Concurrent Java Programs

    NARCIS (Netherlands)

    Mostowski, Wojciech

    2016-01-01

    In this paper we discuss a verification method for concurrent Java programs based on the concept of dynamic frames. We build on our earlier work that proposes a new, symbolic permission system for concurrent reasoning and we provide the following new contributions. First, we describe our approach

  9. Target discrimination method for SAR images based on semisupervised co-training

    Science.gov (United States)

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  10. Crane Safety Assessment Method Based on Entropy and Cumulative Prospect Theory

    Directory of Open Access Journals (Sweden)

    Aihua Li

    2017-01-01

    Full Text Available Assessing the safety status of cranes is an important problem. To overcome the inaccuracies and misjudgments in such assessments, this work describes a safety assessment method for cranes that combines entropy and cumulative prospect theory. Firstly, the proposed method transforms the set of evaluation indices into an evaluation vector. Secondly, a decision matrix is then constructed from the evaluation vectors and evaluation standards, and an entropy-based technique is applied to calculate the index weights. Thirdly, positive and negative prospect value matrices are established from reference points based on the positive and negative ideal solutions. Thus, this enables the crane safety grade to be determined according to the ranked comprehensive prospect values. Finally, the safety status of four general overhead traveling crane samples is evaluated to verify the rationality and feasibility of the proposed method. The results demonstrate that the method described in this paper can precisely and reasonably reflect the safety status of a crane.

  11. Matrix pencil method-based reference current generation for shunt active power filters

    DEFF Research Database (Denmark)

    Terriche, Yacine; Golestan, Saeed; Guerrero, Josep M.

    2018-01-01

    response and works well under distorted and unbalanced voltage. Moreover, the proposed method can estimate the voltage phase accurately; this property enables the algorithm to compensate for both power factor and current unbalance. The effectiveness of the proposed method is verified using simulation...... are using the discrete Fourier transform (DFT) in the frequency domain or the instantaneous p–q theory and the synchronous reference frame in the time domain. The DFT, however, suffers from the picket-fence effect and spectral leakage. On the other hand, the DFT takes at least one cycle of the nominal...... frequency. The time-domain methods show a weakness under voltage distortion, which requires prior filtering techniques. The aim of this study is to present a fast yet effective method for generating the RCC for SAPFs. The proposed method, which is based on the matrix pencil method, has a fast dynamic...

  12. An information theory criteria based blind method for enumerating active users in DS-CDMA system

    Science.gov (United States)

    Samsami Khodadad, Farid; Abed Hodtani, Ghosheh

    2014-11-01

    In this paper, a new and blind algorithm for active user enumeration in asynchronous direct sequence code division multiple access (DS-CDMA) in multipath channel scenario is proposed. The proposed method is based on information theory criteria. There are two main categories of information criteria which are widely used in active user enumeration, Akaike Information Criterion (AIC) and Minimum Description Length (MDL) information theory criteria. The main difference between these two criteria is their penalty functions. Due to this difference, MDL is a consistent enumerator which has better performance in higher signal-to-noise ratios (SNR) but AIC is preferred in lower SNRs. In sequel, we propose a SNR compliance method based on subspace and training genetic algorithm to have the performance of both of them. Moreover, our method uses only a single antenna, in difference to the previous methods which decrease hardware complexity. Simulation results show that the proposed method is capable of estimating the number of active users without any prior knowledge and the efficiency of the method.

  13. Estimation of body fluids with bioimpedance spectroscopy: state of the art methods and proposal of novel methods

    International Nuclear Information System (INIS)

    Buendia, R; Seoane, F; Lindecrantz, K; Bosaeus, I; Gil-Pita, R; Johannsson, G; Ellegård, L; Ward, L C

    2015-01-01

    Determination of body fluids is a useful common practice in determination of disease mechanisms and treatments. Bioimpedance spectroscopy (BIS) methods are non-invasive, inexpensive and rapid alternatives to reference methods such as tracer dilution. However, they are indirect and their robustness and validity are unclear. In this article, state of the art methods are reviewed, their drawbacks identified and new methods are proposed. All methods were tested on a clinical database of patients receiving growth hormone replacement therapy. Results indicated that most BIS methods are similarly accurate (e.g.  <  0.5   ±   3.0% mean percentage difference for total body water) for estimation of body fluids. A new model for calculation is proposed that performs equally well for all fluid compartments (total body water, extra- and intracellular water). It is suggested that the main source of error in extracellular water estimation is due to anisotropy, in total body water estimation to the uncertainty associated with intracellular resistivity and in determination of intracellular water a combination of both. (paper)

  14. Novel Direction Of Arrival Estimation Method Based on Coherent Accumulation Matrix Reconstruction

    Directory of Open Access Journals (Sweden)

    Li Lei

    2015-04-01

    Full Text Available Based on coherent accumulation matrix reconstruction, a novel Direction Of Arrival (DOA estimation decorrelation method of coherent signals is proposed using a small sample. First, the Signal to Noise Ratio (SNR is improved by performing coherent accumulation operation on an array of observed data. Then, according to the structure characteristics of the accumulated snapshot vector, the equivalent covariance matrix, whose rank is the same as the number of array elements, is constructed. The rank of this matrix is proved to be determined just by the number of incident signals, which realize the decorrelation of coherent signals. Compared with spatial smoothing method, the proposed method performs better by effectively avoiding aperture loss with high-resolution characteristics and low computational complexity. Simulation results demonstrate the efficiency of the proposed method.

  15. Breaking a chaos-based secure communication scheme designed by an improved modulation method

    Energy Technology Data Exchange (ETDEWEB)

    Li Shujun [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)]. E-mail: hooklee@mail.com; Alvarez, Gonzalo [Instituto de Fisica Aplicada, Consejo Superior de Investigaciones Cientificas, Serrano 144-28006 Madrid (Spain); Chen Guanrong [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)

    2005-07-01

    Recently Bu and Wang [Bu S, Wang B-H. Chaos, Solitons and Fractals 2004;19(4):919-24] proposed a simple modulation method aiming to improve the security of chaos-based secure communications against return-map-based attacks. Soon this modulation method was independently cryptanalyzed by Chee et al. [Chee CY, Xu D, Bishop SR. Chaos, Solitons and Fractals 2004;21(5):1129-34], Wu et al. [Wu X, Hu H, Zhang B. Chaos, Solitons and Fractals 2004;22(2):367-73], and Alvarez et al. [Alvarez G, Montoya F, Romera M, Pastor G. Chaos, Solitons and Fractals, in press, arXiv:nlin/0406065] via different attacks. As an enhancement to the Bu-Wang method, an improving scheme was suggested by Wu et al. by removing the relationship between the modulating function and the zero-points. The present paper points out that the improved scheme proposed by Wu et al. is still insecure against a new attack. Compared with the existing attacks, the proposed attack is more powerful and can also break the original Bu-Wang scheme. Furthermore, it is pointed out that the security of the modulation-based schemes proposed by Wu et al. is not so satisfactory from a pure cryptographical point of view. The synchronization performance of this class of modulation-based schemes is also discussed.

  16. Breaking a chaos-based secure communication scheme designed by an improved modulation method

    International Nuclear Information System (INIS)

    Li Shujun; Alvarez, Gonzalo; Chen Guanrong

    2005-01-01

    Recently Bu and Wang [Bu S, Wang B-H. Chaos, Solitons and Fractals 2004;19(4):919-24] proposed a simple modulation method aiming to improve the security of chaos-based secure communications against return-map-based attacks. Soon this modulation method was independently cryptanalyzed by Chee et al. [Chee CY, Xu D, Bishop SR. Chaos, Solitons and Fractals 2004;21(5):1129-34], Wu et al. [Wu X, Hu H, Zhang B. Chaos, Solitons and Fractals 2004;22(2):367-73], and Alvarez et al. [Alvarez G, Montoya F, Romera M, Pastor G. Chaos, Solitons and Fractals, in press, arXiv:nlin/0406065] via different attacks. As an enhancement to the Bu-Wang method, an improving scheme was suggested by Wu et al. by removing the relationship between the modulating function and the zero-points. The present paper points out that the improved scheme proposed by Wu et al. is still insecure against a new attack. Compared with the existing attacks, the proposed attack is more powerful and can also break the original Bu-Wang scheme. Furthermore, it is pointed out that the security of the modulation-based schemes proposed by Wu et al. is not so satisfactory from a pure cryptographical point of view. The synchronization performance of this class of modulation-based schemes is also discussed

  17. A permutation-based multiple testing method for time-course microarray experiments

    Directory of Open Access Journals (Sweden)

    George Stephen L

    2009-10-01

    Full Text Available Abstract Background Time-course microarray experiments are widely used to study the temporal profiles of gene expression. Storey et al. (2005 developed a method for analyzing time-course microarray studies that can be applied to discovering genes whose expression trajectories change over time within a single biological group, or those that follow different time trajectories among multiple groups. They estimated the expression trajectories of each gene using natural cubic splines under the null (no time-course and alternative (time-course hypotheses, and used a goodness of fit test statistic to quantify the discrepancy. The null distribution of the statistic was approximated through a bootstrap method. Gene expression levels in microarray data are often complicatedly correlated. An accurate type I error control adjusting for multiple testing requires the joint null distribution of test statistics for a large number of genes. For this purpose, permutation methods have been widely used because of computational ease and their intuitive interpretation. Results In this paper, we propose a permutation-based multiple testing procedure based on the test statistic used by Storey et al. (2005. We also propose an efficient computation algorithm. Extensive simulations are conducted to investigate the performance of the permutation-based multiple testing procedure. The application of the proposed method is illustrated using the Caenorhabditis elegans dauer developmental data. Conclusion Our method is computationally efficient and applicable for identifying genes whose expression levels are time-dependent in a single biological group and for identifying the genes for which the time-profile depends on the group in a multi-group setting.

  18. An Efficient Evolutionary Based Method For Image Segmentation

    OpenAIRE

    Aslanzadeh, Roohollah; Qazanfari, Kazem; Rahmati, Mohammad

    2017-01-01

    The goal of this paper is to present a new efficient image segmentation method based on evolutionary computation which is a model inspired from human behavior. Based on this model, a four layer process for image segmentation is proposed using the split/merge approach. In the first layer, an image is split into numerous regions using the watershed algorithm. In the second layer, a co-evolutionary process is applied to form centers of finals segments by merging similar primary regions. In the t...

  19. A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD

    Directory of Open Access Journals (Sweden)

    J. Tang

    2017-09-01

    Full Text Available Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.

  20. A novel method for human age group classification based on

    Directory of Open Access Journals (Sweden)

    Anuradha Yarlagadda

    2015-10-01

    Full Text Available In the computer vision community, easy categorization of a person’s facial image into various age groups is often quite precise and is not pursued effectively. To address this problem, which is an important area of research, the present paper proposes an innovative method of age group classification system based on the Correlation Fractal Dimension of complex facial image. Wrinkles appear on the face with aging thereby changing the facial edges of the image. The proposed method is rotation and poses invariant. The present paper concentrates on developing an innovative technique that classifies facial images into four categories i.e. child image (0–15, young adult image (15–30, middle-aged adult image (31–50, and senior adult image (>50 based on correlation FD value of a facial edge image.

  1. Logic-based aggregation methods for ranking student applicants

    Directory of Open Access Journals (Sweden)

    Milošević Pavle

    2017-01-01

    Full Text Available In this paper, we present logic-based aggregation models used for ranking student applicants and we compare them with a number of existing aggregation methods, each more complex than the previous one. The proposed models aim to include depen- dencies in the data using Logical aggregation (LA. LA is a aggregation method based on interpolative Boolean algebra (IBA, a consistent multi-valued realization of Boolean algebra. This technique is used for a Boolean consistent aggregation of attributes that are logically dependent. The comparison is performed in the case of student applicants for master programs at the University of Belgrade. We have shown that LA has some advantages over other presented aggregation methods. The software realization of all applied aggregation methods is also provided. This paper may be of interest not only for student ranking, but also for similar problems of ranking people e.g. employees, team members, etc.

  2. Matrix-based image reconstruction methods for tomography

    International Nuclear Information System (INIS)

    Llacer, J.; Meng, J.D.

    1984-10-01

    Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

  3. Statistical Bayesian method for reliability evaluation based on ADT data

    Science.gov (United States)

    Lu, Dawei; Wang, Lizhi; Sun, Yusheng; Wang, Xiaohong

    2018-05-01

    Accelerated degradation testing (ADT) is frequently conducted in the laboratory to predict the products’ reliability under normal operating conditions. Two kinds of methods, degradation path models and stochastic process models, are utilized to analyze degradation data and the latter one is the most popular method. However, some limitations like imprecise solution process and estimation result of degradation ratio still exist, which may affect the accuracy of the acceleration model and the extrapolation value. Moreover, the conducted solution of this problem, Bayesian method, lose key information when unifying the degradation data. In this paper, a new data processing and parameter inference method based on Bayesian method is proposed to handle degradation data and solve the problems above. First, Wiener process and acceleration model is chosen; Second, the initial values of degradation model and parameters of prior and posterior distribution under each level is calculated with updating and iteration of estimation values; Third, the lifetime and reliability values are estimated on the basis of the estimation parameters; Finally, a case study is provided to demonstrate the validity of the proposed method. The results illustrate that the proposed method is quite effective and accuracy in estimating the lifetime and reliability of a product.

  4. A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2015-01-01

    Full Text Available Association rules mining is an important topic in the domain of data mining and knowledge discovering. Some papers have presented several interestingness measure methods; the most typical are Support, Confidence, Lift, Improve, and so forth. But their limitations are obvious, like no objective criterion, lack of statistical base, disability of defining negative relationship, and so forth. This paper proposes three new methods, Bi-lift, Bi-improve, and Bi-confidence, for Lift, Improve, and Confidence, respectively. Then, on the basis of utility function and the executing cost of rules, we propose interestingness function based on profit (IFBP considering subjective preferences and characteristics of specific application object. Finally, a novel measure framework is proposed to improve the traditional one through experimental analysis. In conclusion, the new methods and measure framework are prior to the traditional ones in the aspects of objective criterion, comprehensive definition, and practical application.

  5. Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

    Energy Technology Data Exchange (ETDEWEB)

    Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)

    2015-06-15

    In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

  6. Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

    International Nuclear Information System (INIS)

    Tuvshinjargal, Doopalam; Lee, Deok Jin

    2015-01-01

    In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments

  7. An Improved Information Hiding Method Based on Sparse Representation

    Directory of Open Access Journals (Sweden)

    Minghai Yao

    2015-01-01

    Full Text Available A novel biometric authentication information hiding method based on the sparse representation is proposed for enhancing the security of biometric information transmitted in the network. In order to make good use of abundant information of the cover image, the sparse representation method is adopted to exploit the correlation between the cover and biometric images. Thus, the biometric image is divided into two parts. The first part is the reconstructed image, and the other part is the residual image. The biometric authentication image cannot be restored by any one part. The residual image and sparse representation coefficients are embedded into the cover image. Then, for the sake of causing much less attention of attackers, the visual attention mechanism is employed to select embedding location and embedding sequence of secret information. Finally, the reversible watermarking algorithm based on histogram is utilized for embedding the secret information. For verifying the validity of the algorithm, the PolyU multispectral palmprint and the CASIA iris databases are used as biometric information. The experimental results show that the proposed method exhibits good security, invisibility, and high capacity.

  8. A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

    KAUST Repository

    Liang, Faming

    2013-03-01

    The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate of the parameters is updated accordingly under the framework of stochastic approximation. Since the proposed method makes use of only a small proportion of the data at each iteration, it avoids inverting large covariance matrices and thus is scalable to large datasets. The proposed method also leads to a general parameter estimation approach, maximum mean log-likelihood estimation, which includes the popular maximum (log)-likelihood estimation (MLE) approach as a special case and is expected to play an important role in analyzing large datasets. Under mild conditions, it is shown that the estimator resulting from the proposed method converges in probability to a set of parameter values of equivalent Gaussian probability measures, and that the estimator is asymptotically normally distributed. To the best of the authors\\' knowledge, the present study is the first one on asymptotic normality under infill asymptotics for general covariance functions. The proposed method is illustrated with large datasets, both simulated and real. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  9. Accelerated H-LBP-based edge extraction method for digital radiography

    Energy Technology Data Exchange (ETDEWEB)

    Qiao, Shuang; Zhao, Chen-yi; Huang, Ji-peng [School of Physics, Northeast Normal University, Changchun 130024 (China); Sun, Jia-ning, E-mail: sunjn118@nenu.edu.cn [School of Mathematics and Statistics, Northeast Normal University, Changchun 130024 (China)

    2015-01-11

    With the goal of achieving real time and efficient edge extraction for digital radiography, an accelerated H-LBP-based edge extraction method (AH-LBP) is presented in this paper by improving the existing framework of local binary pattern with the H function (H-LBP). Since the proposed method avoids computationally expensive operations with no loss of quality, it possesses much lower computational complexity than H-LBP. Experimental results on real radiographies show desirable performance of our method. - Highlights: • An accelerated H-LBP method for edge extraction on digital radiography is proposed. • The novel AH-LBP relies on numerical analysis of the existing H-LBP method. • Aiming at accelerating, H-LBP is reformulated as a direct binary processing. • AH-LBP provides the same edge extraction result as H-LBP does. • AH-LBP has low computational complexity satisfying real time requirements.

  10. A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting

    International Nuclear Information System (INIS)

    Azimi, R.; Ghayekhloo, M.; Ghofrani, M.

    2016-01-01

    Highlights: • A novel clustering approach is proposed based on the data transformation approach. • A novel cluster selection method based on correlation analysis is presented. • The proposed hybrid clustering approach leads to deep learning for MLPNN. • A hybrid forecasting method is developed to predict solar radiations. • The evaluation results show superior performance of the proposed forecasting model. - Abstract: Accurate forecasting of renewable energy sources plays a key role in their integration into the grid. This paper proposes a hybrid solar irradiance forecasting framework using a Transformation based K-means algorithm, named TB K-means, to increase the forecast accuracy. The proposed clustering method is a combination of a new initialization technique, K-means algorithm and a new gradual data transformation approach. Unlike the other K-means based clustering methods which are not capable of providing a fixed and definitive answer due to the selection of different cluster centroids for each run, the proposed clustering provides constant results for different runs of the algorithm. The proposed clustering is combined with a time-series analysis, a novel cluster selection algorithm and a multilayer perceptron neural network (MLPNN) to develop the hybrid solar radiation forecasting method for different time horizons (1 h ahead, 2 h ahead, …, 48 h ahead). The performance of the proposed TB K-means clustering is evaluated using several different datasets and compared with different variants of K-means algorithm. Solar datasets with different solar radiation characteristics are also used to determine the accuracy and processing speed of the developed forecasting method with the proposed TB K-means and other clustering techniques. The results of direct comparison with other well-established forecasting models demonstrate the superior performance of the proposed hybrid forecasting method. Furthermore, a comparative analysis with the benchmark solar

  11. A text zero-watermarking method based on keyword dense interval

    Science.gov (United States)

    Yang, Fan; Zhu, Yuesheng; Jiang, Yifeng; Qing, Yin

    2017-07-01

    Digital watermarking has been recognized as a useful technology for the copyright protection and authentication of digital information. However, rarely did the former methods focus on the key content of digital carrier. The idea based on the protection of key content is more targeted and can be considered in different digital information, including text, image and video. In this paper, we use text as research object and a text zero-watermarking method which uses keyword dense interval (KDI) as the key content is proposed. First, we construct zero-watermarking model by introducing the concept of KDI and giving the method of KDI extraction. Second, we design detection model which includes secondary generation of zero-watermark and the similarity computing method of keyword distribution. Besides, experiments are carried out, and the results show that the proposed method gives better performance than other available methods especially in the attacks of sentence transformation and synonyms substitution.

  12. A pre-trained convolutional neural network based method for thyroid nodule diagnosis.

    Science.gov (United States)

    Ma, Jinlian; Wu, Fa; Zhu, Jiang; Xu, Dong; Kong, Dexing

    2017-01-01

    In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, we propose a hybrid method for thyroid nodule diagnosis, which is a fusion of two pre-trained convolutional neural networks (CNNs) with different convolutional layers and fully-connected layers. Firstly, the two networks pre-trained with ImageNet database are separately trained. Secondly, we fuse feature maps learned by trained convolutional filters, pooling and normalization operations of the two CNNs. Finally, with the fused feature maps, a softmax classifier is used to diagnose thyroid nodules. The proposed method is validated on 15,000 ultrasound images collected from two local hospitals. Experiment results show that the proposed CNN based methods can accurately and effectively diagnose thyroid nodules. In addition, the fusion of the two CNN based models lead to significant performance improvement, with an accuracy of 83.02%±0.72%. These demonstrate the potential clinical applications of this method. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. A Copula-Based Method for Estimating Shear Strength Parameters of Rock Mass

    Directory of Open Access Journals (Sweden)

    Da Huang

    2014-01-01

    Full Text Available The shear strength parameters (i.e., the internal friction coefficient f and cohesion c are very important in rock engineering, especially for the stability analysis and reinforcement design of slopes and underground caverns. In this paper, a probabilistic method, Copula-based method, is proposed for estimating the shear strength parameters of rock mass. The optimal Copula functions between rock mass quality Q and f, Q and c for the marbles are established based on the correlation analyses of the results of 12 sets of in situ tests in the exploration adits of Jinping I-Stage Hydropower Station. Although the Copula functions are derived from the in situ tests for the marbles, they can be extended to be applied to other types of rock mass with similar geological and mechanical properties. For another 9 sets of in situ tests as an extensional application, by comparison with the results from Hoek-Brown criterion, the estimated values of f and c from the Copula-based method achieve better accuracy. Therefore, the proposed Copula-based method is an effective tool in estimating rock strength parameters.

  14. Spiking cortical model based non-local means method for despeckling multiframe optical coherence tomography data

    Science.gov (United States)

    Gu, Yameng; Zhang, Xuming

    2017-05-01

    Optical coherence tomography (OCT) images are severely degraded by speckle noise. Existing methods for despeckling multiframe OCT data cannot deliver sufficient speckle suppression while preserving image details well. To address this problem, the spiking cortical model (SCM) based non-local means (NLM) method has been proposed in this letter. In the proposed method, the considered frame and two neighboring frames are input into three SCMs to generate the temporal series of pulse outputs. The normalized moment of inertia (NMI) of the considered patches in the pulse outputs is extracted to represent the rotational and scaling invariant features of the corresponding patches in each frame. The pixel similarity is computed based on the Euclidean distance between the NMI features and used as the weight. Each pixel in the considered frame is restored by the weighted averaging of all pixels in the pre-defined search window in the three frames. Experiments on the real multiframe OCT data of the pig eye demonstrate the advantage of the proposed method over the frame averaging method, the multiscale sparsity based tomographic denoising method, the wavelet-based method and the traditional NLM method in terms of visual inspection and objective metrics such as signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), equivalent number of looks (ENL) and cross-correlation (XCOR).

  15. Image Mosaic Method Based on SIFT Features of Line Segment

    Directory of Open Access Journals (Sweden)

    Jun Zhu

    2014-01-01

    Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  16. A Novel Mobile Personalized Recommended Method Based on Money Flow Model for Stock Exchange

    Directory of Open Access Journals (Sweden)

    Qingzhen Xu

    2014-01-01

    Full Text Available Personalized recommended method is widely used to recommend commodities for target customers in e-commerce sector. The core idea of merchandise personalized recommendation can be applied to financial field, which can also achieve stock personalized recommendation. This paper proposes a new recommended method using collaborative filtering based on user fuzzy clustering and predicts the trend of those stocks based on money flow. We use M/G/1 queue system with multiple vacations and server close-down time to measure practical money flow. Based on the indicated results of money flow, we can select the more valued stock to recommend to investors. The experimental results show that the proposed method provides investors with reliable practical investment guidance and receiving more returns.

  17. Seismic wavefield modeling based on time-domain symplectic and Fourier finite-difference method

    Science.gov (United States)

    Fang, Gang; Ba, Jing; Liu, Xin-xin; Zhu, Kun; Liu, Guo-Chang

    2017-06-01

    Seismic wavefield modeling is important for improving seismic data processing and interpretation. Calculations of wavefield propagation are sometimes not stable when forward modeling of seismic wave uses large time steps for long times. Based on the Hamiltonian expression of the acoustic wave equation, we propose a structure-preserving method for seismic wavefield modeling by applying the symplectic finite-difference method on time grids and the Fourier finite-difference method on space grids to solve the acoustic wave equation. The proposed method is called the symplectic Fourier finite-difference (symplectic FFD) method, and offers high computational accuracy and improves the computational stability. Using acoustic approximation, we extend the method to anisotropic media. We discuss the calculations in the symplectic FFD method for seismic wavefield modeling of isotropic and anisotropic media, and use the BP salt model and BP TTI model to test the proposed method. The numerical examples suggest that the proposed method can be used in seismic modeling of strongly variable velocities, offering high computational accuracy and low numerical dispersion. The symplectic FFD method overcomes the residual qSV wave of seismic modeling in anisotropic media and maintains the stability of the wavefield propagation for large time steps.

  18. Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

    2010-01-01

    of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed...

  19. GRAPH-BASED POST INCIDENT INTERNAL AUDIT METHOD OF COMPUTER EQUIPMENT

    Directory of Open Access Journals (Sweden)

    I. S. Pantiukhin

    2016-05-01

    Full Text Available Graph-based post incident internal audit method of computer equipment is proposed. The essence of the proposed solution consists in the establishing of relationships among hard disk damps (image, RAM and network. This method is intended for description of information security incident properties during the internal post incident audit of computer equipment. Hard disk damps receiving and formation process takes place at the first step. It is followed by separation of these damps into the set of components. The set of components includes a large set of attributes that forms the basis for the formation of the graph. Separated data is recorded into the non-relational database management system (NoSQL that is adapted for graph storage, fast access and processing. Damps linking application method is applied at the final step. The presented method gives the possibility to human expert in information security or computer forensics for more precise, informative internal audit of computer equipment. The proposed method allows reducing the time spent on internal audit of computer equipment, increasing accuracy and informativeness of such audit. The method has a development potential and can be applied along with the other components in the tasks of users’ identification and computer forensics.

  20. Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry

    International Nuclear Information System (INIS)

    Han, Yongming; Geng, Zhiqiang; Zhu, Qunxiong; Qu, Yixin

    2015-01-01

    DEA (data envelopment analysis) has been widely used for the efficiency analysis of industrial production process. However, the conventional DEA model is difficult to analyze the pros and cons of the multi DMUs (decision-making units). The DEACM (DEA cross-model) can distinguish the pros and cons of the effective DMUs, but it is unable to take the effect of the uncertainty data into account. This paper proposes an efficiency analysis method based on FDEACM (fuzzy DEA cross-model) with Fuzzy Data. The proposed method has better objectivity and resolving power for the decision-making. First we obtain the minimum, the median and the maximum values of the multi-criteria ethylene energy consumption data by the data fuzzification. On the basis of the multi-criteria fuzzy data, the benchmark of the effective production situations and the improvement directions of the ineffective of the ethylene plants under different production data configurations are obtained by the FDEACM. The experimental result shows that the proposed method can improve the ethylene production conditions and guide the efficiency of energy utilization during ethylene production process. - Highlights: • This paper proposes an efficiency analysis method based on FDEACM (fuzzy DEA cross-model) with data fuzzification. • The proposed method is more efficient and accurate than other methods. • We obtain an energy efficiency analysis framework and process based on FDEACM in ethylene production industry. • The proposed method is valid and efficient in improvement of energy efficiency in the ethylene plants

  1. A Proposal of Operational Risk Management Method Using FMEA for Drug Manufacturing Computerized System

    Science.gov (United States)

    Takahashi, Masakazu; Nanba, Reiji; Fukue, Yoshinori

    This paper proposes operational Risk Management (RM) method using Failure Mode and Effects Analysis (FMEA) for drug manufacturing computerlized system (DMCS). The quality of drug must not be influenced by failures and operational mistakes of DMCS. To avoid such situation, DMCS has to be conducted enough risk assessment and taken precautions. We propose operational RM method using FMEA for DMCS. To propose the method, we gathered and compared the FMEA results of DMCS, and develop a list that contains failure modes, failures and countermeasures. To apply this list, we can conduct RM in design phase, find failures, and conduct countermeasures efficiently. Additionally, we can find some failures that have not been found yet.

  2. A proposal on evaluation method of neutron absorption performance to substitute conventional neutron attenuation test

    International Nuclear Information System (INIS)

    Kim, Je Hyun; Shim, Chang Ho; Kim, Sung Hyun; Choe, Jung Hun; Cho, In Hak; Park, Hwan Seo; Park, Hyun Seo; Kim, Jung Ho; Kim, Yoon Ho

    2016-01-01

    For a verification of newly-developed neutron absorbers, one of guidelines on the qualification and acceptance of neutron absorbers is the neutron attenuation test. However, this approach can cause a problem for the qualifications that it cannot distinguish how the neutron attenuates from materials. In this study, an estimation method of neutron absorption performances for materials is proposed to detect both direct penetration and back-scattering neutrons. For the verification of the proposed method, MCNP simulations with the experimental system designed in this study were pursued using the polyethylene, iron, normal glass and the vitrified form. The results show that it can easily test neutron absorption ability using single absorber model. Also, from simulation results of single absorber and double absorbers model, it is verified that the proposed method can evaluate not only the direct thermal neutrons passing through materials, but also the scattered neutrons reflected to the materials. Therefore, the neutron absorption performances can be accurately estimated using the proposed method comparing with the conventional neutron attenuation test. It is expected that the proposed method can contribute to increase the reliability of the performance of neutron absorbers

  3. A proposal on evaluation method of neutron absorption performance to substitute conventional neutron attenuation test

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Je Hyun; Shim, Chang Ho [Dept. of Nuclear Engineering, Hanyang University, Seoul (Korea, Republic of); Kim, Sung Hyun [Nuclear Fuel Cycle Waste Treatment Research Division, Research Reactor Institute, Kyoto University, Osaka (Japan); Choe, Jung Hun; Cho, In Hak; Park, Hwan Seo [Ionizing Radiation Center, Nuclear Fuel Cycle Waste Treatment Research Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Park, Hyun Seo; Kim, Jung Ho; Kim, Yoon Ho [Ionizing Radiation Center, Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

    2016-12-15

    For a verification of newly-developed neutron absorbers, one of guidelines on the qualification and acceptance of neutron absorbers is the neutron attenuation test. However, this approach can cause a problem for the qualifications that it cannot distinguish how the neutron attenuates from materials. In this study, an estimation method of neutron absorption performances for materials is proposed to detect both direct penetration and back-scattering neutrons. For the verification of the proposed method, MCNP simulations with the experimental system designed in this study were pursued using the polyethylene, iron, normal glass and the vitrified form. The results show that it can easily test neutron absorption ability using single absorber model. Also, from simulation results of single absorber and double absorbers model, it is verified that the proposed method can evaluate not only the direct thermal neutrons passing through materials, but also the scattered neutrons reflected to the materials. Therefore, the neutron absorption performances can be accurately estimated using the proposed method comparing with the conventional neutron attenuation test. It is expected that the proposed method can contribute to increase the reliability of the performance of neutron absorbers.

  4. A new method to identify the foot of continental slope based on an integrated profile analysis

    Science.gov (United States)

    Wu, Ziyin; Li, Jiabiao; Li, Shoujun; Shang, Jihong; Jin, Xiaobin

    2017-06-01

    A new method is proposed to identify automatically the foot of the continental slope (FOS) based on the integrated analysis of topographic profiles. Based on the extremum points of the second derivative and the Douglas-Peucker algorithm, it simplifies the topographic profiles, then calculates the second derivative of the original profiles and the D-P profiles. Seven steps are proposed to simplify the original profiles. Meanwhile, multiple identification methods are proposed to determine the FOS points, including gradient, water depth and second derivative values of data points, as well as the concave and convex, continuity and segmentation of the topographic profiles. This method can comprehensively and intelligently analyze the topographic profiles and their derived slopes, second derivatives and D-P profiles, based on which, it is capable to analyze the essential properties of every single data point in the profile. Furthermore, it is proposed to remove the concave points of the curve and in addition, to implement six FOS judgment criteria.

  5. An Image Encryption Method Based on Bit Plane Hiding Technology

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; LI Zhitang; TU Hao

    2006-01-01

    A novel image hiding method based on the correlation analysis of bit plane is described in this paper. Firstly, based on the correlation analysis, different bit plane of a secret image is hided in different bit plane of several different open images. And then a new hiding image is acquired by a nesting "Exclusive-OR" operation on those images obtained from the first step. At last, by employing image fusion technique, the final hiding result is achieved. The experimental result shows that the method proposed in this paper is effective.

  6. Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials.

    Science.gov (United States)

    Liu, Wei; Zhang, Bo; Zhang, Hui; Zhang, Zhiwei

    2017-04-01

    There is growing interest in assessing immune biomarkers, which are quick to measure and potentially predictive of long-term efficacy, as surrogate endpoints in randomized, placebo-controlled vaccine trials. This can be done under a principal stratification approach, with principal strata defined using a subject's potential immune responses to vaccine and placebo (the latter may be assumed to be zero). In this context, principal surrogacy refers to the extent to which vaccine efficacy varies across principal strata. Because a placebo recipient's potential immune response to vaccine is unobserved in a standard vaccine trial, augmented vaccine trials have been proposed to produce the information needed to evaluate principal surrogacy. This article reviews existing methods based on an estimated likelihood and a pseudo-score (PS) and proposes two new methods based on a semiparametric likelihood (SL) and a pseudo-likelihood (PL), for analyzing augmented vaccine trials. Unlike the PS method, the SL method does not require a model for missingness, which can be advantageous when immune response data are missing by happenstance. The SL method is shown to be asymptotically efficient, and it performs similarly to the PS and PL methods in simulation experiments. The PL method appears to have a computational advantage over the PS and SL methods.

  7. Deterministic and fuzzy-based methods to evaluate community resilience

    Science.gov (United States)

    Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

    2018-04-01

    Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

  8. Topology optimization based on the harmony search method

    International Nuclear Information System (INIS)

    Lee, Seung-Min; Han, Seog-Young

    2017-01-01

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  9. Topology optimization based on the harmony search method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Min; Han, Seog-Young [Hanyang University, Seoul (Korea, Republic of)

    2017-06-15

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  10. Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

    Directory of Open Access Journals (Sweden)

    Dayong Zhou

    2008-12-01

    Full Text Available Tsatsanis and Xu have applied the constrained minimum output variance (CMOV principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

  11. A Newton-Based Extremum Seeking MPPT Method for Photovoltaic Systems with Stochastic Perturbations

    Directory of Open Access Journals (Sweden)

    Heng Li

    2014-01-01

    Full Text Available Microcontroller based maximum power point tracking (MPPT has been the most popular MPPT approach in photovoltaic systems due to its high flexibility and efficiency in different photovoltaic systems. It is well known that PV systems typically operate under a range of uncertain environmental parameters and disturbances, which implies that MPPT controllers generally suffer from some unknown stochastic perturbations. To address this issue, a novel Newton-based stochastic extremum seeking MPPT method is proposed. Treating stochastic perturbations as excitation signals, the proposed MPPT controller has a good tolerance of stochastic perturbations in nature. Different from conventional gradient-based extremum seeking MPPT algorithm, the convergence rate of the proposed controller can be totally user-assignable rather than determined by unknown power map. The stability and convergence of the proposed controller are rigorously proved. We further discuss the effects of partial shading and PV module ageing on the proposed controller. Numerical simulations and experiments are conducted to show the effectiveness of the proposed MPPT algorithm.

  12. Modulation transfer function (MTF) measurement method based on support vector machine (SVM)

    Science.gov (United States)

    Zhang, Zheng; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

    2016-03-01

    An imaging system's spatial quality can be expressed by the system's modulation spread function (MTF) as a function of spatial frequency in terms of the linear response theory. Methods have been proposed to assess the MTF of an imaging system using point, slit or edge techniques. The edge method is widely used for the low requirement of targets. However, the traditional edge methods are limited by the edge angle. Besides, image noise will impair the measurement accuracy, making the measurement result unstable. In this paper, a novel measurement method based on the support vector machine (SVM) is proposed. Image patches with different edge angles and MTF levels are generated as the training set. Parameters related with MTF and image structure are extracted from the edge images. Trained with image parameters and the corresponding MTF, the SVM classifier can assess the MTF of any edge image. The result shows that the proposed method has an excellent performance on measuring accuracy and stability.

  13. Activity-Based Costing Using Multicriteria Drivers: An Accounting Proposal to Boost Companies Toward Sustainability

    Directory of Open Access Journals (Sweden)

    Heitor F. Marinho Neto

    2018-05-01

    Full Text Available Recognizing that natural environment is reaching its maximum limits in providing resources and diluting the waste generated by human production systems, efforts toward more sustainable production systems are mandatory to secure the development of future generations. For this purpose, changing the productivity model adopted by companies that are almost exclusively rooted on circulating money to generate profit, named business as usual, is an important issue. In this sense, an alternative would be establishing the relationship of stocks and flows of energy, material, and information with environmental, economic and social outcomes, thus resulting in new accounting approaches. This work aims to propose an activity-based costing (ABC based on multicriteria drivers including economic, emissions, and emergy (with an “m” values. The proposed ABC costing allocates each one of the multicriteria drivers into a specific part of the sustainability conceptual model, in an attempt to embrace a holistic perspective and allow for a sustainable-based decision, rather than considering purely economic drivers. The goal programming (GP method is considered so as to support a decision based on multicriteria aspects. Results show that the proposed accounting approach known as ABCsustain allows for decisions toward a company's sustainability by acting on both the amount and kind of a company's product that should be managed, as well as on the effective increase of a specific company's activity or process. The proposed ABCsustain could make the insertion of environmental issues into companies strategic planning more effective. It is expected that environmental issues go beyond a simple diagnoses and begin to be considered as action in factum in the companies' decisions toward achieving a more sustainable world system.

  14. Online sequential condition prediction method of natural circulation systems based on EOS-ELM and phase space reconstruction

    International Nuclear Information System (INIS)

    Chen, Hanying; Gao, Puzhen; Tan, Sichao; Tang, Jiguo; Yuan, Hongsheng

    2017-01-01

    Highlights: •An online condition prediction method for natural circulation systems in NPP was proposed based on EOS-ELM. •The proposed online prediction method was validated using experimental data. •The training speed of the proposed method is significantly fast. •The proposed method can achieve good accuracy in wide parameter range. -- Abstract: Natural circulation design is widely used in the passive safety systems of advanced nuclear power reactors. The irregular and chaotic flow oscillations are often observed in boiling natural circulation systems so it is difficult for operators to monitor and predict the condition of these systems. An online condition forecasting method for natural circulation system is proposed in this study as an assisting technique for plant operators. The proposed prediction approach was developed based on Ensemble of Online Sequential Extreme Learning Machine (EOS-ELM) and phase space reconstruction. Online Sequential Extreme Learning Machine (OS-ELM) is an online sequential learning neural network algorithm and EOS-ELM is the ensemble method of it. The proposed condition prediction method can be initiated by a small chunk of monitoring data and it can be updated by newly arrived data at very fast speed during the online prediction. Simulation experiments were conducted on the data of two natural circulation loops to validate the performance of the proposed method. The simulation results show that the proposed predication model can successfully recognize different types of flow oscillations and accurately forecast the trend of monitored plant variables. The influence of the number of hidden nodes and neural network inputs on prediction performance was studied and the proposed model can achieve good accuracy in a wide parameter range. Moreover, the comparison results show that the proposed condition prediction method has much faster online learning speed and better prediction accuracy than conventional neural network model.

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

    Science.gov (United States)

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

    2018-02-01

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

  16. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  17. A deep learning-based multi-model ensemble method for cancer prediction.

    Science.gov (United States)

    Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

    2018-01-01

    Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. A multicore based parallel image registration method.

    Science.gov (United States)

    Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L; Foran, David J

    2009-01-01

    Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform.

  19. A physically based catchment partitioning method for hydrological analysis

    Science.gov (United States)

    Menduni, Giovanni; Riboni, Vittoria

    2000-07-01

    We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

  20. Fault feature analysis of cracked gear based on LOD and analytical-FE method

    Science.gov (United States)

    Wu, Jiateng; Yang, Yu; Yang, Xingkai; Cheng, Junsheng

    2018-01-01

    At present, there are two main ideas for gear fault diagnosis. One is the model-based gear dynamic analysis; the other is signal-based gear vibration diagnosis. In this paper, a method for fault feature analysis of gear crack is presented, which combines the advantages of dynamic modeling and signal processing. Firstly, a new time-frequency analysis method called local oscillatory-characteristic decomposition (LOD) is proposed, which has the attractive feature of extracting fault characteristic efficiently and accurately. Secondly, an analytical-finite element (analytical-FE) method which is called assist-stress intensity factor (assist-SIF) gear contact model, is put forward to calculate the time-varying mesh stiffness (TVMS) under different crack states. Based on the dynamic model of the gear system with 6 degrees of freedom, the dynamic simulation response was obtained for different tooth crack depths. For the dynamic model, the corresponding relation between the characteristic parameters and the degree of the tooth crack is established under a specific condition. On the basis of the methods mentioned above, a novel gear tooth root crack diagnosis method which combines the LOD with the analytical-FE is proposed. Furthermore, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) are contrasted with the LOD by gear crack fault vibration signals. The analysis results indicate that the proposed method performs effectively and feasibility for the tooth crack stiffness calculation and the gear tooth crack fault diagnosis.

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

    Directory of Open Access Journals (Sweden)

    Mulian Zheng

    2017-03-01

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

  2. Sensitivity-based virtual fields for the non-linear virtual fields method

    Science.gov (United States)

    Marek, Aleksander; Davis, Frances M.; Pierron, Fabrice

    2017-09-01

    The virtual fields method is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non-linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was corrupted by noise.

  3. An imbalance fault detection method based on data normalization and EMD for marine current turbines.

    Science.gov (United States)

    Zhang, Milu; Wang, Tianzhen; Tang, Tianhao; Benbouzid, Mohamed; Diallo, Demba

    2017-05-01

    This paper proposes an imbalance fault detection method based on data normalization and Empirical Mode Decomposition (EMD) for variable speed direct-drive Marine Current Turbine (MCT) system. The method is based on the MCT stator current under the condition of wave and turbulence. The goal of this method is to extract blade imbalance fault feature, which is concealed by the supply frequency and the environment noise. First, a Generalized Likelihood Ratio Test (GLRT) detector is developed and the monitoring variable is selected by analyzing the relationship between the variables. Then, the selected monitoring variable is converted into a time series through data normalization, which makes the imbalance fault characteristic frequency into a constant. At the end, the monitoring variable is filtered out by EMD method to eliminate the effect of turbulence. The experiments show that the proposed method is robust against turbulence through comparing the different fault severities and the different turbulence intensities. Comparison with other methods, the experimental results indicate the feasibility and efficacy of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Hybrid modelling framework by using mathematics-based and information-based methods

    International Nuclear Information System (INIS)

    Ghaboussi, J; Kim, J; Elnashai, A

    2010-01-01

    Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

  5. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

    Science.gov (United States)

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-12-13

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

  6. A Matrix Method Based on the Fibonacci Polynomials to the Generalized Pantograph Equations with Functional Arguments

    Directory of Open Access Journals (Sweden)

    Ayşe Betül Koç

    2014-01-01

    Full Text Available A pseudospectral method based on the Fibonacci operational matrix is proposed to solve generalized pantograph equations with linear functional arguments. By using this method, approximate solutions of the problems are easily obtained in form of the truncated Fibonacci series. Some illustrative examples are given to verify the efficiency and effectiveness of the proposed method. Then, the numerical results are compared with other methods.

  7. Approach to Multi-Criteria Group Decision-Making Problems Based on the Best-Worst-Method and ELECTRE Method

    Directory of Open Access Journals (Sweden)

    Xinshang You

    2016-09-01

    Full Text Available This paper proposes a novel approach to cope with the multi-criteria group decision-making problems. We give the pairwise comparisons based on the best-worst-method (BWM, which can decrease comparison times. Additionally, our comparison results are determined with the positive and negative aspects. In order to deal with the decision matrices effectively, we consider the elimination and choice translation reality (ELECTRE III method under the intuitionistic multiplicative preference relations environment. The ELECTRE III method is designed for a double-automatic system. Under a certain limitation, without bothering the decision-makers to reevaluate the alternatives, this system can adjust some special elements that have the most influence on the group’s satisfaction degree. Moreover, the proposed method is suitable for both the intuitionistic multiplicative preference relation and the interval valued fuzzy preference relations through the transformation formula. An illustrative example is followed to demonstrate the rationality and availability of the novel method.

  8. An Automata Based Intrusion Detection Method for Internet of Things

    Directory of Open Access Journals (Sweden)

    Yulong Fu

    2017-01-01

    Full Text Available Internet of Things (IoT transforms network communication to Machine-to-Machine (M2M basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

  9. Spherical aberration compensation method for long focal-length measurement based on Talbot interferometry

    Science.gov (United States)

    Luo, Yupeng; Huang, Xiao; Bai, Jian; Du, Juan; Liu, Qun; Luo, Yujie; Luo, Jia

    2017-08-01

    Large-aperture and long focal-length lens is widely used in high energy laser system. The method based on Talbot interferometry is a reliable method to measure the focal length of such elements. By employing divergent beam and two gratings of different periods, this method could realize full-aperture measurement, higher accuracy and better repeatability. However, it does not take into account the spherical aberration of the measured lens resulting in the moiré fringes bending, which will introduce measurement error. Furthermore, in long-focal measurement with divergent beam, this error is an important factor affecting the measurement accuracy. In this paper, we propose a new spherical aberration compensation method, which could significantly reduce the measurement error. Characterized by central-symmetric scanning window, the proposed method is based on the relationship between spherical aberration and the lens aperture. Angle data of moiré fringes in each scanning window is retrieved by Fourier analysis and statistically fitted to estimate a globally optimum value for spherical-aberration-free focal length calculation. Simulation and experiment have been carried out. Compared to the previous work, the proposed method is able to reduce the relative measurement error by 50%. The effect of scanning window size and shift step length on the results is also discussed.

  10. Efficient depth intraprediction method for H.264/AVC-based three-dimensional video coding

    Science.gov (United States)

    Oh, Kwan-Jung; Oh, Byung Tae

    2015-04-01

    We present an intracoding method that is applicable to depth map coding in multiview plus depth systems. Our approach combines skip prediction and plane segmentation-based prediction. The proposed depth intraskip prediction uses the estimated direction at both the encoder and decoder, and does not need to encode residual data. Our plane segmentation-based intraprediction divides the current block into biregions, and applies a different prediction scheme for each segmented region. This method avoids incorrect estimations across different regions, resulting in higher prediction accuracy. Simulation results demonstrate that the proposed scheme is superior to H.264/advanced video coding intraprediction and has the ability to improve the subjective rendering quality.

  11. A simple method for detecting tumor in T2-weighted MRI brain images. An image-based analysis

    International Nuclear Information System (INIS)

    Lau, Phooi-Yee; Ozawa, Shinji

    2006-01-01

    The objective of this paper is to present a decision support system which uses a computer-based procedure to detect tumor blocks or lesions in digitized medical images. The authors developed a simple method with a low computation effort to detect tumors on T2-weighted Magnetic Resonance Imaging (MRI) brain images, focusing on the connection between the spatial pixel value and tumor properties from four different perspectives: cases having minuscule differences between two images using a fixed block-based method, tumor shape and size using the edge and binary images, tumor properties based on texture values using spatial pixel intensity distribution controlled by a global discriminate value, and the occurrence of content-specific tumor pixel for threshold images. Measurements of the following medical datasets were performed: different time interval images, and different brain disease images on single and multiple slice images. Experimental results have revealed that our proposed technique incurred an overall error smaller than those in other proposed methods. In particular, the proposed method allowed decrements of false alarm and missed alarm errors, which demonstrate the effectiveness of our proposed technique. In this paper, we also present a prototype system, known as PCB, to evaluate the performance of the proposed methods by actual experiments, comparing the detection accuracy and system performance. (author)

  12. Integral-equation based methods for parameter estimation in output pulses of radiation detectors: Application in nuclear medicine and spectroscopy

    Science.gov (United States)

    Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

    2018-04-01

    Model based analysis methods are relatively new approaches for processing the output data of radiation detectors in nuclear medicine imaging and spectroscopy. A class of such methods requires fast algorithms for fitting pulse models to experimental data. In order to apply integral-equation based methods for processing the preamplifier output pulses, this article proposes a fast and simple method for estimating the parameters of the well-known bi-exponential pulse model by solving an integral equation. The proposed method needs samples from only three points of the recorded pulse as well as its first and second order integrals. After optimizing the sampling points, the estimation results were calculated and compared with two traditional integration-based methods. Different noise levels (signal-to-noise ratios from 10 to 3000) were simulated for testing the functionality of the proposed method, then it was applied to a set of experimental pulses. Finally, the effect of quantization noise was assessed by studying different sampling rates. Promising results by the proposed method endorse it for future real-time applications.

  13. A novel ECG data compression method based on adaptive Fourier decomposition

    Science.gov (United States)

    Tan, Chunyu; Zhang, Liming

    2017-12-01

    This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

  14. New Multi-Criteria Group Decision-Making Method Based on Vague Set Theory

    OpenAIRE

    Kuo-Sui Lin

    2016-01-01

    In light of the deficiencies and limitations for existing score functions, Lin has proposed a more effective and reasonable new score function for measuring vague values. By using Lin’s score function and a new weighted aggregation score function, an algorithm for multi-criteria group decision-making method was proposed to solve vague set based group decision-making problems under vague environments. Finally, a numerical example was illustrated to show the effectiveness of the proposed multi-...

  15. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  16. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  17. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  18. A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery

    Directory of Open Access Journals (Sweden)

    Fasahat Ullah Siddiqui

    2016-07-01

    Full Text Available Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality. Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state

  19. Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

    Science.gov (United States)

    Sahran, Shahnorbanun; Albashish, Dheeb; Abdullah, Azizi; Shukor, Nordashima Abd; Hayati Md Pauzi, Suria

    2018-04-18

    Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are important tissue components. However, it is difficult to represent the high-dimensional textures of these tissue components. To solve this problem, we propose a new FS method that enables the selection of features with minimal redundancy in the tissue components. We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC. We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods. We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to

  20. An information hiding method based on LSB and tent chaotic map

    Science.gov (United States)

    Song, Jianhua; Ding, Qun

    2011-06-01

    In order to protect information security more effectively, a novel information hiding method based on LSB and Tent chaotic map was proposed, first the secret message is Tent chaotic encrypted, and then LSB steganography is executed for the encrypted message in the cover-image. Compared to the traditional image information hiding method, the simulation results indicate that the method greatly improved in imperceptibility and security, and acquired good results.

  1. Reliability Evaluation of Bridges Based on Nonprobabilistic Response Surface Limit Method

    OpenAIRE

    Chen, Xuyong; Chen, Qian; Bian, Xiaoya; Fan, Jianping

    2017-01-01

    Due to many uncertainties in nonprobabilistic reliability assessment of bridges, the limit state function is generally unknown. The traditional nonprobabilistic response surface method is a lengthy and oscillating iteration process and leads to difficultly solving the nonprobabilistic reliability index. This article proposes a nonprobabilistic response surface limit method based on the interval model. The intention of this method is to solve the upper and lower limits of the nonprobabilistic ...

  2. MR-based synthetic CT generation using a deep convolutional neural network method.

    Science.gov (United States)

    Han, Xiao

    2017-04-01

    Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN

  3. A variable capacitance based modeling and power capability predicting method for ultracapacitor

    Science.gov (United States)

    Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

    2018-01-01

    Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

  4. An efficient hole-filling method based on depth map in 3D view generation

    Science.gov (United States)

    Liang, Haitao; Su, Xiu; Liu, Yilin; Xu, Huaiyuan; Wang, Yi; Chen, Xiaodong

    2018-01-01

    New virtual view is synthesized through depth image based rendering(DIBR) using a single color image and its associated depth map in 3D view generation. Holes are unavoidably generated in the 2D to 3D conversion process. We propose a hole-filling method based on depth map to address the problem. Firstly, we improve the process of DIBR by proposing a one-to-four (OTF) algorithm. The "z-buffer" algorithm is used to solve overlap problem. Then, based on the classical patch-based algorithm of Criminisi et al., we propose a hole-filling algorithm using the information of depth map to handle the image after DIBR. In order to improve the accuracy of the virtual image, inpainting starts from the background side. In the calculation of the priority, in addition to the confidence term and the data term, we add the depth term. In the search for the most similar patch in the source region, we define the depth similarity to improve the accuracy of searching. Experimental results show that the proposed method can effectively improve the quality of the 3D virtual view subjectively and objectively.

  5. An evidence-based patient-centered method makes the biopsychosocial model scientific.

    Science.gov (United States)

    Smith, Robert C; Fortin, Auguste H; Dwamena, Francesca; Frankel, Richard M

    2013-06-01

    To review the scientific status of the biopsychosocial (BPS) model and to propose a way to improve it. Engel's BPS model added patients' psychological and social health concerns to the highly successful biomedical model. He proposed that the BPS model could make medicine more scientific, but its use in education, clinical care, and, especially, research remains minimal. Many aver correctly that the present model cannot be defined in a consistent way for the individual patient, making it untestable and non-scientific. This stems from not obtaining relevant BPS data systematically, where one interviewer obtains the same information another would. Recent research by two of the authors has produced similar patient-centered interviewing methods that are repeatable and elicit just the relevant patient information needed to define the model at each visit. We propose that the field adopt these evidence-based methods as the standard for identifying the BPS model. Identifying a scientific BPS model in each patient with an agreed-upon, evidence-based patient-centered interviewing method can produce a quantum leap ahead in both research and teaching. A scientific BPS model can give us more confidence in being humanistic. In research, we can conduct more rigorous studies to inform better practices. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

    Science.gov (United States)

    Yin, Shibin; Ren, Yongjie; Zhu, Jigui; Yang, Shourui; Ye, Shenghua

    2013-01-01

    A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system. PMID:24300597

  7. A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection

    Directory of Open Access Journals (Sweden)

    Xingling Shao

    2014-01-01

    Full Text Available A novel method of robust trajectory linearization control for a class of nonlinear systems with uncertainties based on disturbance rejection is proposed. Firstly, on the basis of trajectory linearization control (TLC method, a feedback linearization based control law is designed to transform the original tracking error dynamics to the canonical integral-chain form. To address the issue of reducing the influence made by uncertainties, with tracking error as input, linear extended state observer (LESO is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. Meanwhile, the boundedness of the estimated error is investigated by theoretical analysis. In addition, decoupled controller (which has the characteristic of well-tuning and simple form based on LESO is synthesized to realize the output tracking for closed-loop system. The closed-loop stability of the system under the proposed LESO-based control structure is established. Also, simulation results are presented to illustrate the effectiveness of the control strategy.

  8. Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

    NARCIS (Netherlands)

    Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, J.

    2016-01-01

    We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

  9. A new method to predict the metadynamic recrystallization behavior in a typical nickel-based superalloy

    International Nuclear Information System (INIS)

    Lin, Y.C.; Chen, Xiao-Min; Chen, Ming-Song; Wen, Dong-Xu; Zhou, Ying; He, Dao-Guang

    2016-01-01

    The metadynamic recrystallization (MDRX) behaviors of a typical nickel-based superalloy are investigated by two-pass hot compression tests and four conventional stress-based conventional approaches (offset stress method, back-extrapolation stress method, peak stress method, and mean stress method). It is found that the conventional stress-based methods are not suitable to evaluate the MDRX softening fractions for the studied superalloy. Therefore, a new approach, 'maximum stress method', is proposed to evaluate the MDRX softening fraction. Based on the proposed method, the effects of deformation temperature, strain rate, initial average grain size, and interpass time on MDRX behaviors are discussed in detail. Results show that MDRX softening fraction is sensitive to deformation parameters. The MDRX softening fraction rapidly increases with the increase of deformation temperature, strain rate, and interpass time. The MDRX softening fraction in the coarse-grain material is lower than that in the fine-grain material. Moreover, the observed microstructures indicate that the initial coarse grains can be effectively refined by MDRX. Based on the experimental results, the kinetics equations are established and validated to describe the MDRX behaviors of the studied superalloy. (orig.)

  10. Contribution for an Urban Geomorphoheritage Assessment Method: Proposal from Three Geomorphosites in Rome (Italy

    Directory of Open Access Journals (Sweden)

    Pica Alessia

    2017-09-01

    Full Text Available Urban geomorphology has important implications in spatial planning of human activities, and it also has a geotouristic potential due to the relationship between cultural and geomorphological heritage. Despite the introduction of the term Anthropocene to describe the deep influence that human activities have had in recent times on Earth evolution, urban geomorphological heritage studies are relatively rare and limited and urban geotourism development is recent. The analysis of the complex urban landscape often need the integration of multidisciplinary data. This study aims to propose the first urban geomorphoheritage assessment method, which originates after long-lasting previous geomorphological and geotouristic studies on Rome city centre, it depict rare examples of the geomorphological mapping of a metropolis and, at the same time, of an inventory of urban geomorphosites. The proposal is applied to geomorphosites in the Esquilino neighbourhood of Rome, whose analysis confirm the need for an ad hoc method for assessing urban geomorphosites, as already highlighted in the most recent literature on the topic. The urban geomorphoheritage assessment method is based on: (i the urban geomorphological analysis by means of multitemporal and multidisciplinary data; (ii the geomorphosite inventory; and (iii the geomorphoheritage assessment and enhancement. One challenge is to assess invisible geomorphosites that are widespread in urban context. To this aim, we reworked the attributes describing the Value of a site for Geotourism in order to build up a specific methodology for the analysis of the urban geomorphological heritage.

  11. A Method for Harmonic Sources Detection based on Harmonic Distortion Power Rate

    Science.gov (United States)

    Lin, Ruixing; Xu, Lin; Zheng, Xian

    2018-03-01

    Harmonic sources detection at the point of common coupling is an essential step for harmonic contribution determination and harmonic mitigation. The harmonic distortion power rate index is proposed for harmonic source location based on IEEE Std 1459-2010 in the paper. The method only based on harmonic distortion power is not suitable when the background harmonic is large. To solve this problem, a threshold is determined by the prior information, when the harmonic distortion power is larger than the threshold, the customer side is considered as the main harmonic source, otherwise, the utility side is. A simple model of public power system was built in MATLAB/Simulink and field test results of typical harmonic loads verified the effectiveness of proposed method.

  12. OCL-BASED TEST CASE GENERATION USING CATEGORY PARTITIONING METHOD

    Directory of Open Access Journals (Sweden)

    A. Jalila

    2015-10-01

    Full Text Available The adoption of fault detection techniques during initial stages of software development life cycle urges to improve reliability of a software product. Specification-based testing is one of the major criterions to detect faults in the requirement specification or design of a software system. However, due to the non-availability of implementation details, test case generation from formal specifications become a challenging task. As a novel approach, the proposed work presents a methodology to generate test cases from OCL (Object constraint Language formal specification using Category Partitioning Method (CPM. The experiment results indicate that the proposed methodology is more effective in revealing specification based faults. Furthermore, it has been observed that OCL and CPM form an excellent combination for performing functional testing at the earliest to improve software quality with reduced cost.

  13. Star tracking method based on multiexposure imaging for intensified star trackers.

    Science.gov (United States)

    Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

    2017-07-20

    The requirements for the dynamic performance of star trackers are rapidly increasing with the development of space exploration technologies. However, insufficient knowledge of the angular acceleration has largely decreased the performance of the existing star tracking methods, and star trackers may even fail to track under highly dynamic conditions. This study proposes a star tracking method based on multiexposure imaging for intensified star trackers. The accurate estimation model of the complete motion parameters, including the angular velocity and angular acceleration, is established according to the working characteristic of multiexposure imaging. The estimation of the complete motion parameters is utilized to generate the predictive star image accurately. Therefore, the correct matching and tracking between stars in the real and predictive star images can be reliably accomplished under highly dynamic conditions. Simulations with specific dynamic conditions are conducted to verify the feasibility and effectiveness of the proposed method. Experiments with real starry night sky observation are also conducted for further verification. Simulations and experiments demonstrate that the proposed method is effective and shows excellent performance under highly dynamic conditions.

  14. Proposal for an Evaluation Method for the Performance of Work Procedures.

    Science.gov (United States)

    Mohammed, Mouda; Mébarek, Djebabra; Wafa, Boulagouas; Makhlouf, Chati

    2016-12-01

    Noncompliance of operators with work procedures is a recurrent problem. This human behavior has been said to be situational and studied by many different approaches (ergonomic and others), which consider the noncompliance with work procedures to be obvious and seek to analyze its causes as well as consequences. The object of the proposed method is to solve this problem by focusing on the performance of work procedures and ensuring improved performance on a continuous basis. This study has multiple results: (1) assessment of the work procedures' performance by a multicriteria approach; (2) the use of a continuous improvement approach as a framework for the sustainability of the assessment method of work procedures' performance; and (3) adaptation of the Stop-Card as a facilitator support for continuous improvement of work procedures. The proposed method emphasizes to put in value the inputs of continuous improvement of the work procedures in relation with the conventional approaches which adopt the obvious evidence of the noncompliance to the working procedures and seek to analyze the cause-effect relationships related to this unacceptable phenomenon, especially in strategic industry.

  15. Method of Monitoring Urban Area Deformation Based on Differential TomoSAR

    Directory of Open Access Journals (Sweden)

    WANG Aichun

    2016-12-01

    Full Text Available While the use of differential TomoSAR based on compressive sensing (CS makes it possible to solve the layover problem and reconstruct the deformation information of an observed urban area scene acquired by moderate-high resolution SAR satellite, the performance of the reconstruction decreases for a sparse and structural observed scene due to ignoring the structural characteristics of the observed scene. To deal with this issue, the method for differential SAR tomography based on Khatri-Rao subspace and block compressive sensing (KRS-BCS is proposed. The proposed method changes the reconstruction of the sparse and structural observed scene into a BCS problem under Khatri-Rao subspace, using the structure information of the observed scene and Khatri-Rao product property of the reconstructed observation matrix for differential TomoSAR, such that the KRS-BCS problem is efficiently solved with a block sparse l1/l2 norm optimization signal model, and the performance of resolution capability and reconstruction estimation is compared and analyzed qualitatively and quantitatively by the theoretical analysis and the simulation experiments, all of the results show the propose KRS-BCS method practicably overcomes the problems of CS method, as well as, quite maintains the high resolution characteristics, effectively reduces the probability of false scattering target and greatly improves the reconstruction accurate of scattering point. Finally, the application is taking the urban area of the Mobara(in Chiba, Japan as the test area and using 34 ENVISAT-ASAR images, the accuracy is verifying with the reference deformations derived from first level point data and GPS tracking data, the results show the trend is consistent and the overall deviation is small between reconstruction deformations of the propose KRS-BCS method and the reference deformations, and the accuracy is high in the estimation of the urban area deformation.

  16. Numerical Analysis of Hydrodynamics for Bionic Oscillating Hydrofoil Based on Panel Method

    Directory of Open Access Journals (Sweden)

    Gang Xue

    2016-01-01

    Full Text Available The kinematics model based on the Slender-Body theory is proposed from the bionic movement of real fish. The Panel method is applied to the hydrodynamic performance analysis innovatively, with the Gauss-Seidel method to solve the Navier-Stokes equations additionally, to evaluate the flexible deformation of fish in swimming accurately when satisfying the boundary conditions. A physical prototype to mimic the shape of tuna is developed with the revolutionized technology of rapid prototyping manufacturing. The hydrodynamic performance for rigid oscillating hydrofoil is analyzed with the proposed method, and it shows good coherence with the cases analyzed by the commercial software Fluent and the experimental data from robofish. Furthermore, the hydrodynamic performance of coupled hydrofoil, which consisted of flexible fish body and rigid caudal fin, is analyzed with the proposed method. It shows that the caudal fin has great influence on trailing vortex shedding and the phase angle is the key factor on hydrodynamic performance. It is verified that the shape of trailing vortex is similar to the image of the motion curve at the trailing edge as the assumption of linear vortex plane under the condition of small downwash velocity. The numerical analysis of hydrodynamics for bionic movement based on the Panel method has certain value to reveal the fish swimming mechanism.

  17. An image-based automatic recognition method for the flowering stage of maize

    Science.gov (United States)

    Yu, Zhenghong; Zhou, Huabing; Li, Cuina

    2018-03-01

    In this paper, we proposed an image-based approach for automatic recognizing the flowering stage of maize. A modified HOG/SVM detection framework is first adopted to detect the ears of maize. Then, we use low-rank matrix recovery technology to precisely extract the ears at pixel level. At last, a new feature called color gradient histogram, as an indicator, is proposed to determine the flowering stage. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

  18. The improved business valuation model for RFID company based on the community mining method.

    Science.gov (United States)

    Li, Shugang; Yu, Zhaoxu

    2017-01-01

    Nowadays, the appetite for the investment and mergers and acquisitions (M&A) activity in RFID companies is growing rapidly. Although the huge number of papers have addressed the topic of business valuation models based on statistical methods or neural network methods, only a few are dedicated to constructing a general framework for business valuation that improves the performance with network graph (NG) and the corresponding community mining (CM) method. In this study, an NG based business valuation model is proposed, where real options approach (ROA) integrating CM method is designed to predict the company's net profit as well as estimate the company value. Three improvements are made in the proposed valuation model: Firstly, our model figures out the credibility of the node belonging to each community and clusters the network according to the evolutionary Bayesian method. Secondly, the improved bacterial foraging optimization algorithm (IBFOA) is adopted to calculate the optimized Bayesian posterior probability function. Finally, in IBFOA, bi-objective method is used to assess the accuracy of prediction, and these two objectives are combined into one objective function using a new Pareto boundary method. The proposed method returns lower forecasting error than 10 well-known forecasting models on 3 different time interval valuing tasks for the real-life simulation of RFID companies.

  19. A Pansharpening Method Based on HCT and Joint Sparse Model

    Directory of Open Access Journals (Sweden)

    XU Ning

    2016-04-01

    Full Text Available A novel fusion method based on the hyperspherical color transformation (HCT and joint sparsity model is proposed for decreasing the spectral distortion of fused image further. In the method, an intensity component and angles of each band of the multispectral image is obtained by HCT firstly, and then the intensity component is fused with the panchromatic image through wavelet transform and joint sparsity model. In the joint sparsity model, the redundant and complement information of the different images can be efficiently extracted and employed to yield the high quality results. Finally, the fused multi spectral image is obtained by inverse transforms of wavelet and HCT on the new lower frequency image and the angle components, respectively. Experimental results on Pleiades-1 and WorldView-2 satellites indicate that the proposed method achieves remarkable results.

  20. A numerical method to solve the 1D and the 2D reaction diffusion equation based on Bessel functions and Jacobian free Newton-Krylov subspace methods

    Science.gov (United States)

    Parand, K.; Nikarya, M.

    2017-11-01

    In this paper a novel method will be introduced to solve a nonlinear partial differential equation (PDE). In the proposed method, we use the spectral collocation method based on Bessel functions of the first kind and the Jacobian free Newton-generalized minimum residual (JFNGMRes) method with adaptive preconditioner. In this work a nonlinear PDE has been converted to a nonlinear system of algebraic equations using the collocation method based on Bessel functions without any linearization, discretization or getting the help of any other methods. Finally, by using JFNGMRes, the solution of the nonlinear algebraic system is achieved. To illustrate the reliability and efficiency of the proposed method, we solve some examples of the famous Fisher equation. We compare our results with other methods.

  1. Photonic arbitrary waveform generator based on Taylor synthesis method

    DEFF Research Database (Denmark)

    Liao, Shasha; Ding, Yunhong; Dong, Jianji

    2016-01-01

    Arbitrary waveform generation has been widely used in optical communication, radar system and many other applications. We propose and experimentally demonstrate a silicon-on-insulator (SOI) on chip optical arbitrary waveform generator, which is based on Taylor synthesis method. In our scheme......, a Gaussian pulse is launched to some cascaded microrings to obtain first-, second- and third-order differentiations. By controlling amplitude and phase of the initial pulse and successive differentiations, we can realize an arbitrary waveform generator according to Taylor expansion. We obtain several typical...... waveforms such as square waveform, triangular waveform, flat-top waveform, sawtooth waveform, Gaussian waveform and so on. Unlike other schemes based on Fourier synthesis or frequency-to-time mapping, our scheme is based on Taylor synthesis method. Our scheme does not require any spectral disperser or large...

  2. A Timed Colored Petri Net Simulation-Based Self-Adaptive Collaboration Method for Production-Logistics Systems

    Directory of Open Access Journals (Sweden)

    Zhengang Guo

    2017-03-01

    Full Text Available Complex and customized manufacturing requires a high level of collaboration between production and logistics in a flexible production system. With the widespread use of Internet of Things technology in manufacturing, a great amount of real-time and multi-source manufacturing data and logistics data is created, that can be used to perform production-logistics collaboration. To solve the aforementioned problems, this paper proposes a timed colored Petri net simulation-based self-adaptive collaboration method for Internet of Things-enabled production-logistics systems. The method combines the schedule of token sequences in the timed colored Petri net with real-time status of key production and logistics equipment. The key equipment is made ‘smart’ to actively publish or request logistics tasks. An integrated framework based on a cloud service platform is introduced to provide the basis for self-adaptive collaboration of production-logistics systems. A simulation experiment is conducted by using colored Petri nets (CPN Tools to validate the performance and applicability of the proposed method. Computational experiments demonstrate that the proposed method outperforms the event-driven method in terms of reductions of waiting time, makespan, and electricity consumption. This proposed method is also applicable to other manufacturing systems to implement production-logistics collaboration.

  3. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

    Directory of Open Access Journals (Sweden)

    Qiyang Xiao

    2016-12-01

    Full Text Available In this study, a small leak detection method based on variational mode decomposition (VMD and ambiguity correlation classification (ACC is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF, an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM and back propagation neural network (BP methods.

  4. Passive ranging using a filter-based non-imaging method based on oxygen absorption.

    Science.gov (United States)

    Yu, Hao; Liu, Bingqi; Yan, Zongqun; Zhang, Yu

    2017-10-01

    To solve the problem of poor real-time measurement caused by a hyperspectral imaging system and to simplify the design in passive ranging technology based on oxygen absorption spectrum, a filter-based non-imaging ranging method is proposed. In this method, three bandpass filters are used to obtain the source radiation intensities that are located in the oxygen absorption band near 762 nm and the band's left and right non-absorption shoulders, and a photomultiplier tube is used as the non-imaging sensor of the passive ranging system. Range is estimated by comparing the calculated values of band-average transmission due to oxygen absorption, τ O 2 , against the predicted curve of τ O 2 versus range. The method is tested under short-range conditions. Accuracy of 6.5% is achieved with the designed experimental ranging system at the range of 400 m.

  5. Based on Penalty Function Method

    Directory of Open Access Journals (Sweden)

    Ishaq Baba

    2015-01-01

    Full Text Available The dual response surface for simultaneously optimizing the mean and variance models as separate functions suffers some deficiencies in handling the tradeoffs between bias and variance components of mean squared error (MSE. In this paper, the accuracy of the predicted response is given a serious attention in the determination of the optimum setting conditions. We consider four different objective functions for the dual response surface optimization approach. The essence of the proposed method is to reduce the influence of variance of the predicted response by minimizing the variability relative to the quality characteristics of interest and at the same time achieving the specific target output. The basic idea is to convert the constraint optimization function into an unconstraint problem by adding the constraint to the original objective function. Numerical examples and simulations study are carried out to compare performance of the proposed method with some existing procedures. Numerical results show that the performance of the proposed method is encouraging and has exhibited clear improvement over the existing approaches.

  6. A sediment graph model based on SCS-CN method

    Science.gov (United States)

    Singh, P. K.; Bhunya, P. K.; Mishra, S. K.; Chaube, U. C.

    2008-01-01

    SummaryThis paper proposes new conceptual sediment graph models based on coupling of popular and extensively used methods, viz., Nash model based instantaneous unit sediment graph (IUSG), soil conservation service curve number (SCS-CN) method, and Power law. These models vary in their complexity and this paper tests their performance using data of the Nagwan watershed (area = 92.46 km 2) (India). The sensitivity of total sediment yield and peak sediment flow rate computations to model parameterisation is analysed. The exponent of the Power law, β, is more sensitive than other model parameters. The models are found to have substantial potential for computing sediment graphs (temporal sediment flow rate distribution) as well as total sediment yield.

  7. Analytical method for optimization of maintenance policy based on available system failure data

    International Nuclear Information System (INIS)

    Coria, V.H.; Maximov, S.; Rivas-Dávalos, F.; Melchor, C.L.; Guardado, J.L.

    2015-01-01

    An analytical optimization method for preventive maintenance (PM) policy with minimal repair at failure, periodic maintenance, and replacement is proposed for systems with historical failure time data influenced by a current PM policy. The method includes a new imperfect PM model based on Weibull distribution and incorporates the current maintenance interval T 0 and the optimal maintenance interval T to be found. The Weibull parameters are analytically estimated using maximum likelihood estimation. Based on this model, the optimal number of PM and the optimal maintenance interval for minimizing the expected cost over an infinite time horizon are also analytically determined. A number of examples are presented involving different failure time data and current maintenance intervals to analyze how the proposed analytical optimization method for periodic PM policy performances in response to changes in the distribution of the failure data and the current maintenance interval. - Highlights: • An analytical optimization method for preventive maintenance (PM) policy is proposed. • A new imperfect PM model is developed. • The Weibull parameters are analytically estimated using maximum likelihood. • The optimal maintenance interval and number of PM are also analytically determined. • The model is validated by several numerical examples

  8. EP BASED PSO METHOD FOR SOLVING PROFIT BASED MULTI AREA UNIT COMMITMENT PROBLEM

    Directory of Open Access Journals (Sweden)

    K. VENKATESAN

    2015-04-01

    Full Text Available This paper presents a new approach to solve the profit based multi area unit commitment problem (PBMAUCP using an evolutionary programming based particle swarm optimization (EPPSO method. The objective of this paper is to maximize the profit of generation companies (GENCOs with considering system social benefit. The proposed method helps GENCOs to make a decision, how much power and reserve should be sold in markets, and how to schedule generators in order to receive the maximum profit. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. The tie line transfer limits were considered as a set of constraints during optimization process to ensure the system security and reliability. The overall algorithm can be implemented on an IBM PC, which can process a fairly large system in a reasonable period of time. Case study of four areas with different load pattern each containing 7 units (NTPS and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the profit of evolutionary programming-based particle swarm optimization method (EPPSO with conventional dynamic programming (DP, evolutionary programming (EP, and particle swarm optimization (PSO method. Experimental results shows that the application of this evolutionary programming based particle swarm optimization method have the potential to solve profit based multi area unit commitment problem with lesser computation time.

  9. Quantitative electromechanical impedance method for nondestructive testing based on a piezoelectric bimorph cantilever

    International Nuclear Information System (INIS)

    Fu, Ji; Tan, Chi; Li, Faxin

    2015-01-01

    The electromechanical impedance (EMI) method, which holds great promise in structural health monitoring (SHM), is usually treated as a qualitative method. In this work, we proposed a quantitative EMI method based on a piezoelectric bimorph cantilever using the sample’s local contact stiffness (LCS) as the identification parameter for nondestructive testing (NDT). Firstly, the equivalent circuit of the contact vibration system was established and the analytical relationship between the cantilever’s contact resonance frequency and the LCS was obtained. As the LCS is sensitive to typical defects such as voids and delamination, the proposed EMI method can then be used for NDT. To verify the equivalent circuit model, two piezoelectric bimorph cantilevers were fabricated and their free resonance frequencies were measured and compared with theoretical predictions. It was found that the stiff cantilever’s EMI can be well predicted by the equivalent circuit model while the soft cantilever’s cannot. Then, both cantilevers were assembled into a homemade NDT system using a three-axis motorized stage for LCS scanning. Testing results on a specimen with a prefabricated defect showed that the defect could be clearly reproduced in the LCS image, indicating the validity of the quantitative EMI method for NDT. It was found that the single-frequency mode of the EMI method can also be used for NDT, which is faster but not quantitative. Finally, several issues relating to the practical application of the NDT method were discussed. The proposed EMI-based NDT method offers a simple and rapid solution for damage evaluation in engineering structures and may also shed some light on EMI-based SHM. (paper)

  10. A Method to Measure the Bracelet Based on Feature Energy

    Science.gov (United States)

    Liu, Hongmin; Li, Lu; Wang, Zhiheng; Huo, Zhanqiang

    2017-12-01

    To measure the bracelet automatically, a novel method based on feature energy is proposed. Firstly, the morphological method is utilized to preprocess the image, and the contour consisting of a concentric circle is extracted. Then, a feature energy function, which is relevant to the distances from one pixel to the edge points, is defined taking into account the geometric properties of the concentric circle. The input image is subsequently transformed to the feature energy distribution map (FEDM) by computing the feature energy of each pixel. The center of the concentric circle is thus located by detecting the maximum on the FEDM; meanwhile, the radii of the concentric circle are determined according to the feature energy function of the center pixel. Finally, with the use of a calibration template, the internal diameter and thickness of the bracelet are measured. The experimental results show that the proposed method can measure the true sizes of the bracelet accurately with the simplicity, directness and robustness compared to the existing methods.

  11. Yet Another Method for Image Segmentation based on Histograms and Heuristics

    Directory of Open Access Journals (Sweden)

    Horia-Nicolai L. Teodorescu

    2012-07-01

    Full Text Available We introduce a method for image segmentation that requires little computations, yet providing comparable results to other methods. While the proposed method resembles to the known ones based on histograms, it is still different in the use of the gray level distribution. When to the basic procedure we add several heuristic rules, the method produces results that, in some cases, may outperform the results produced by the known methods. The paper reports preliminary results. More details on the method, improvements, and results will be presented in a future paper.

  12. Proposed method to calculate FRMAC intervention levels for the assessment of radiologically contaminated food and comparison of the proposed method to the U.S. FDA's method to calculate derived intervention levels

    Energy Technology Data Exchange (ETDEWEB)

    Kraus, Terrence D.; Hunt, Brian D.

    2014-02-01

    This report reviews the method recommended by the U.S. Food and Drug Administration for calculating Derived Intervention Levels (DILs) and identifies potential improvements to the DIL calculation method to support more accurate ingestion pathway analyses and protective action decisions. Further, this report proposes an alternate method for use by the Federal Emergency Radiological Assessment Center (FRMAC) to calculate FRMAC Intervention Levels (FILs). The default approach of the FRMAC during an emergency response is to use the FDA recommended methods. However, FRMAC recommends implementing the FIL method because we believe it to be more technically accurate. FRMAC will only implement the FIL method when approved by the FDA representative on the Federal Advisory Team for Environment, Food, and Health.

  13. A BHR Composite Network-Based Visualization Method for Deformation Risk Level of Underground Space.

    Directory of Open Access Journals (Sweden)

    Wei Zheng

    Full Text Available This study proposes a visualization processing method for the deformation risk level of underground space. The proposed method is based on a BP-Hopfield-RGB (BHR composite network. Complex environmental factors are integrated in the BP neural network. Dynamic monitoring data are then automatically classified in the Hopfield network. The deformation risk level is combined with the RGB color space model and is displayed visually in real time, after which experiments are conducted with the use of an ultrasonic omnidirectional sensor device for structural deformation monitoring. The proposed method is also compared with some typical methods using a benchmark dataset. Results show that the BHR composite network visualizes the deformation monitoring process in real time and can dynamically indicate dangerous zones.

  14. A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification

    Science.gov (United States)

    Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia

    With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.

  15. An efficient digital signal processing method for RRNS-based DS-CDMA systems

    Directory of Open Access Journals (Sweden)

    Peter Olsovsky

    2017-09-01

    Full Text Available This paper deals with an efficient method for achieving low power and high speed in advanced Direct-Sequence Code Division Multiple-Access (DS-CDMA wireless communication systems based on the Residue Number System (RNS. A modified algorithm for multiuser DS-CDMA signal generation in MATLAB is proposed and investigated. The most important characteristics of the generated PN code are also presented. Subsequently, a DS-CDMA system based on the combination of the RNS or the so-called Redundant Residue Number System (RRNS is proposed. The enhanced method using a spectrally efficient 8-PSK data modulation scheme to improve the bandwidth efficiency for RRNS-based DS-CDMA systems is presented. By using the C-measure (complexity measure of the error detection function, it is possible to estimate the size of the circuit. Error detection function in RRNSs can be efficiently implemented by LookUp Table (LUT cascades.

  16. Optical image encryption method based on incoherent imaging and polarized light encoding

    Science.gov (United States)

    Wang, Q.; Xiong, D.; Alfalou, A.; Brosseau, C.

    2018-05-01

    We propose an incoherent encoding system for image encryption based on a polarized encoding method combined with an incoherent imaging. Incoherent imaging is the core component of this proposal, in which the incoherent point-spread function (PSF) of the imaging system serves as the main key to encode the input intensity distribution thanks to a convolution operation. An array of retarders and polarizers is placed on the input plane of the imaging structure to encrypt the polarized state of light based on Mueller polarization calculus. The proposal makes full use of randomness of polarization parameters and incoherent PSF so that a multidimensional key space is generated to deal with illegal attacks. Mueller polarization calculus and incoherent illumination of imaging structure ensure that only intensity information is manipulated. Another key advantage is that complicated processing and recording related to a complex-valued signal are avoided. The encoded information is just an intensity distribution, which is advantageous for data storage and transition because information expansion accompanying conventional encryption methods is also avoided. The decryption procedure can be performed digitally or using optoelectronic devices. Numerical simulation tests demonstrate the validity of the proposed scheme.

  17. Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

    Science.gov (United States)

    Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

    2017-05-01

    Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

  18. The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

    Directory of Open Access Journals (Sweden)

    Liang Shen

    2017-01-01

    Full Text Available There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K-shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

  19. Proposal of adaptive human interface and study of interface evaluation method for plant operators

    International Nuclear Information System (INIS)

    Ujita, Hiroshi; Kubota, Ryuji.

    1994-01-01

    In this report, a new concept of human interface adaptive to plant operators' mental model, cognitive process and psychological state which change with time is proposed. It is composed of a function to determine information which should be indicated to operators based on the plant situation, a function to estimate operators' internal conditions, and a function to arrange the information amount, position, timing, form etc. based on their conditions. The method to evaluate the fitness of the interface by using the analysis results based on cognitive science, ergonomics, psychology and physiology is developed to achieve such an interface. Fundamental physiological experiments have been performed. Stress and workload can be identified by the ratio of the power average of the α wave fraction of a brain wave and be distinguished by the ratio of the standard deviation of the R-R interval in test and at rest, in the case of low stress such as mouse operation, calculation and walking. (author)

  20. Proposal of adaptive human interface and study of interface evaluation method for plant operators

    Energy Technology Data Exchange (ETDEWEB)

    Ujita, Hiroshi [Hitachi Ltd., Ibaraki (Japan). Energy Research Lab.; Kubota, Ryuji

    1994-07-01

    In this report, a new concept of human interface adaptive to plant operators' mental model, cognitive process and psychological state which change with time is proposed. It is composed of a function to determine information which should be indicated to operators based on the plant situation, a function to estimate operators' internal conditions, and a function to arrange the information amount, position, timing, form etc. based on their conditions. The method to evaluate the fitness of the interface by using the analysis results based on cognitive science, ergonomics, psychology and physiology is developed to achieve such an interface. Fundamental physiological experiments have been performed. Stress and workload can be identified by the ratio of the power average of the [alpha] wave fraction of a brain wave and be distinguished by the ratio of the standard deviation of the R-R interval in test and at rest, in the case of low stress such as mouse operation, calculation and walking. (author).

  1. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  2. M-Arctan estimator based on the trust-region method

    Energy Technology Data Exchange (ETDEWEB)

    Hassaine, Yacine; Delourme, Benoit; Panciatici, Patrick [Gestionnaire du Reseau de Transport d Electricite Departement Methodes et appui Immeuble Le Colbert 9, Versailles Cedex (France); Walter, Eric [Laboratoire des signaux et systemes (L2S) Supelec, Gif-sur-Yvette (France)

    2006-11-15

    In this paper a new approach is proposed to increase the robustness of the classical L{sub 2}-norm state estimation. To achieve this task a new formulation of the Levemberg-Marquardt algorithm based on the trust-region method is applied to a new M-estimator, which we called M-Arctan. Results obtained on IEEE networks up to 300 buses are presented. (author)

  3. Large-scale Comparative Study of Hi-C-based Chromatin 3D Structure Modeling Methods

    KAUST Repository

    Wang, Cheng

    2018-05-17

    Chromatin is a complex polymer molecule in eukaryotic cells, primarily consisting of DNA and histones. Many works have shown that the 3D folding of chromatin structure plays an important role in DNA expression. The recently proposed Chro- mosome Conformation Capture technologies, especially the Hi-C assays, provide us an opportunity to study how the 3D structures of the chromatin are organized. Based on the data from Hi-C experiments, many chromatin 3D structure modeling methods have been proposed. However, there is limited ground truth to validate these methods and no robust chromatin structure alignment algorithms to evaluate the performance of these methods. In our work, we first made a thorough literature review of 25 publicly available population Hi-C-based chromatin 3D structure modeling methods. Furthermore, to evaluate and to compare the performance of these methods, we proposed a novel data simulation method, which combined the population Hi-C data and single-cell Hi-C data without ad hoc parameters. Also, we designed a global and a local alignment algorithms to measure the similarity between the templates and the chromatin struc- tures predicted by different modeling methods. Finally, the results from large-scale comparative tests indicated that our alignment algorithms significantly outperform the algorithms in literature.

  4. A postprocessing method based on high-resolution spectral estimation for FDTD calculation of phononic band structures

    Energy Technology Data Exchange (ETDEWEB)

    Su Xiaoxing, E-mail: xxsu@bjtu.edu.c [School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044 (China); Li Jianbao; Wang Yuesheng [Institute of Engineering Mechanics, Beijing Jiaotong University, Beijing 100044 (China)

    2010-05-15

    If the energy bands of a phononic crystal are calculated by the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT), good estimation of the eigenfrequencies can only be ensured by the postprocessing of sufficiently long time series generated by a large number of FDTD iterations. In this paper, a postprocessing method based on the high-resolution spectral estimation via the Yule-Walker method is proposed to overcome this difficulty. Numerical simulation results for three-dimensional acoustic and two-dimensional elastic systems show that, compared with the classic FFT-based postprocessing method, the proposed method can give much better estimation of the eigenfrequencies when the FDTD is run with relatively few iterations.

  5. A postprocessing method based on high-resolution spectral estimation for FDTD calculation of phononic band structures

    International Nuclear Information System (INIS)

    Su Xiaoxing; Li Jianbao; Wang Yuesheng

    2010-01-01

    If the energy bands of a phononic crystal are calculated by the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT), good estimation of the eigenfrequencies can only be ensured by the postprocessing of sufficiently long time series generated by a large number of FDTD iterations. In this paper, a postprocessing method based on the high-resolution spectral estimation via the Yule-Walker method is proposed to overcome this difficulty. Numerical simulation results for three-dimensional acoustic and two-dimensional elastic systems show that, compared with the classic FFT-based postprocessing method, the proposed method can give much better estimation of the eigenfrequencies when the FDTD is run with relatively few iterations.

  6. Qualitative methods in radiography research: a proposed framework

    International Nuclear Information System (INIS)

    Adams, J.; Smith, T.

    2003-01-01

    Introduction: While radiography is currently developing a research base, which is important in terms of professional development and informing practice and policy issues in the field, the amount of research published by radiographers remains limited. However, a range of qualitative methods offer further opportunities for radiography research. Purpose: This paper briefly introduces a number of key qualitative methods (qualitative interviews, focus groups, observational methods, diary methods and document/text analysis) and sketches one possible framework for future qualitative work in radiography research. The framework focuses upon three areas for study: intra-professional issues; inter-professional issues; and clinical practice, patient and health delivery issues. While the paper outlines broad areas for future focus rather than providing a detailed protocol for how individual pieces of research should be conducted, a few research questions have been chosen and examples of possible qualitative methods required to answer such questions are outlined for each area. Conclusion: Given the challenges and opportunities currently facing the development of a research base within radiography, the outline of key qualitative methods and broad areas suitable for their application is offered as a useful tool for those within the profession looking to embark upon or enhance their research career

  7. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  8. The attitude inversion method of geostationary satellites based on unscented particle filter

    Science.gov (United States)

    Du, Xiaoping; Wang, Yang; Hu, Heng; Gou, Ruixin; Liu, Hao

    2018-04-01

    The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.

  9. Reliability Evaluation of Bridges Based on Nonprobabilistic Response Surface Limit Method

    Directory of Open Access Journals (Sweden)

    Xuyong Chen

    2017-01-01

    Full Text Available Due to many uncertainties in nonprobabilistic reliability assessment of bridges, the limit state function is generally unknown. The traditional nonprobabilistic response surface method is a lengthy and oscillating iteration process and leads to difficultly solving the nonprobabilistic reliability index. This article proposes a nonprobabilistic response surface limit method based on the interval model. The intention of this method is to solve the upper and lower limits of the nonprobabilistic reliability index and to narrow the range of the nonprobabilistic reliability index. If the range of the reliability index reduces to an acceptable accuracy, the solution will be considered convergent, and the nonprobabilistic reliability index will be obtained. The case study indicates that using the proposed method can avoid oscillating iteration process, make iteration process stable and convergent, reduce iteration steps significantly, and improve computational efficiency and precision significantly compared with the traditional nonprobabilistic response surface method. Finally, the nonprobabilistic reliability evaluation process of bridge will be built through evaluating the reliability of one PC continuous rigid frame bridge with three spans using the proposed method, which appears to be more simple and reliable when lack of samples and parameters in the bridge nonprobabilistic reliability evaluation is present.

  10. Variable aperture-based ptychographical iterative engine method

    Science.gov (United States)

    Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

    2018-02-01

    A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches.

  11. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  12. Study on highly efficient seismic data acquisition and processing methods based on sparsity constraint

    Science.gov (United States)

    Wang, H.; Chen, S.; Tao, C.; Qiu, L.

    2017-12-01

    High-density, high-fold and wide-azimuth seismic data acquisition methods are widely used to overcome the increasingly sophisticated exploration targets. The acquisition period is longer and longer and the acquisition cost is higher and higher. We carry out the study of highly efficient seismic data acquisition and processing methods based on sparse representation theory (or compressed sensing theory), and achieve some innovative results. The theoretical principles of highly efficient acquisition and processing is studied. We firstly reveal sparse representation theory based on wave equation. Then we study the highly efficient seismic sampling methods and present an optimized piecewise-random sampling method based on sparsity prior information. At last, a reconstruction strategy with the sparsity constraint is developed; A two-step recovery approach by combining sparsity-promoting method and hyperbolic Radon transform is also put forward. The above three aspects constitute the enhanced theory of highly efficient seismic data acquisition. The specific implementation strategies of highly efficient acquisition and processing are studied according to the highly efficient acquisition theory expounded in paragraph 2. Firstly, we propose the highly efficient acquisition network designing method by the help of optimized piecewise-random sampling method. Secondly, we propose two types of highly efficient seismic data acquisition methods based on (1) single sources and (2) blended (or simultaneous) sources. Thirdly, the reconstruction procedures corresponding to the above two types of highly efficient seismic data acquisition methods are proposed to obtain the seismic data on the regular acquisition network. A discussion of the impact on the imaging result of blended shooting is discussed. In the end, we implement the numerical tests based on Marmousi model. The achieved results show: (1) the theoretical framework of highly efficient seismic data acquisition and processing

  13. Knowledge management method for knowledge based BWR Core Operation Management System

    Energy Technology Data Exchange (ETDEWEB)

    Wada, Yutaka; Fukuzaki, Takaharu; Kobayashi, Yasuhiro

    1989-03-01

    A knowledge management method is proposed to support an except whose knowledge is stored in a knowledge base in the BWR Core Operation Management System. When the alterations in the operation plans are motivated by the expert after evaluating them, the method attempts to find the knowledge which must be modified and to give the expert guidances. In this way the resultant operation plans are improved by modifying values of referenced data. Using data dependency among data, which are defined and referred during inference, data to be modified are retrieved. In generating modification guidances, data reference and definition procedures are classified by syntactic analysis of knowledge. The modified data values are calculated with a sensitivity between the increment in the data to be modified and the resultant one in the performance of operation plans. The efficiency of the knowledge management by the proposed method, when applied to the knowledge based system including 500 pieces of knowledge for BWR control rod programming, is higher than that for interactive use of existing general purpose editors. (author).

  14. Knowledge management method for knowledge based BWR Core Operation Management System

    International Nuclear Information System (INIS)

    Wada, Yutaka; Fukuzaki, Takaharu; Kobayashi, Yasuhiro

    1989-01-01

    A knowledge management method is proposed to support an except whose knowledge is stored in a knowledge base in the BWR Core Operation Management System. When the alterations in the operation plans are motivated by the expert after evaluating them, the method attempts to find the knowledge which must be modified and to give the expert guidances. In this way the resultant operation plans are improved by modifying values of referenced data. Using data dependency among data, which are defined and referred during inference, data to be modified are retrieved. In generating modification guidances, data reference and definition procedures are classified by syntactic analysis of knowledge. The modified data values are calculated with a sensitivity between the increment in the data to be modified and the resultant one in the performance of operation plans. The efficiency of the knowledge management by the proposed method, when applied to the knowledge based system including 500 pieces of knowledge for BWR control rod programming, is higher than that for interactive use of existing general purpose editors. (author)

  15. Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

    Directory of Open Access Journals (Sweden)

    Qingwu Gong

    2017-03-01

    Full Text Available The intermittency and variability of permeated distributed generators (DGs could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not supplied, PLC (probability of load curtailment, EFLC (expected frequency of load curtailment, and SI (severity index—were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs’ output power, an improved PEM (point estimate method-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

  16. Congestion management of electric distribution networks through market based methods

    DEFF Research Database (Denmark)

    Huang, Shaojun

     EVs and HPs. Market-based congestion management methods are the focus of the thesis. They handle the potential congestion at the energy planning stage; therefore, the aggregators can optimally plan the energy consumption and have the least impact on the customers. After reviewing and identifying...... the shortcomings of the existing methods, the thesis fully studies and improves the dynamic tariff (DT) method, and proposes two  new market-based  congestion management methods,  namely the  dynamic subsidy (DS) method and the flexible demand swap method. The thesis improves the DT method from four aspects......Rapidly increasing share of intermittent renewable energy production poses a great challenge of the management and operation of the modern power systems. Deployment of a large number of flexible demands, such as electrical vehicles (EVs) and heat pumps (HPs), is believed to be a promising solution...

  17. Hybrid Modeling Method for a DEP Based Particle Manipulation

    Directory of Open Access Journals (Sweden)

    Mohamad Sawan

    2013-01-01

    Full Text Available In this paper, a new modeling approach for Dielectrophoresis (DEP based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.

  18. A method of mobile video transmission based on J2ee

    Science.gov (United States)

    Guo, Jian-xin; Zhao, Ji-chun; Gong, Jing; Chun, Yang

    2013-03-01

    As 3G (3rd-generation) networks evolve worldwide, the rising demand for mobile video services and the enormous growth of video on the internet is creating major new revenue opportunities for mobile network operators and application developers. The text introduced a method of mobile video transmission based on J2ME, giving the method of video compressing, then describing the video compressing standard, and then describing the software design. The proposed mobile video method based on J2EE is a typical mobile multimedia application, which has a higher availability and a wide range of applications. The users can get the video through terminal devices such as phone.

  19. Scatter measurement and correction method for cone-beam CT based on single grating scan

    Science.gov (United States)

    Huang, Kuidong; Shi, Wenlong; Wang, Xinyu; Dong, Yin; Chang, Taoqi; Zhang, Hua; Zhang, Dinghua

    2017-06-01

    In cone-beam computed tomography (CBCT) systems based on flat-panel detector imaging, the presence of scatter significantly reduces the quality of slices. Based on the concept of collimation, this paper presents a scatter measurement and correction method based on single grating scan. First, according to the characteristics of CBCT imaging, the scan method using single grating and the design requirements of the grating are analyzed and figured out. Second, by analyzing the composition of object projection images and object-and-grating projection images, the processing method for the scatter image at single projection angle is proposed. In addition, to avoid additional scan, this paper proposes an angle interpolation method of scatter images to reduce scan cost. Finally, the experimental results show that the scatter images obtained by this method are accurate and reliable, and the effect of scatter correction is obvious. When the additional object-and-grating projection images are collected and interpolated at intervals of 30 deg, the scatter correction error of slices can still be controlled within 3%.

  20. Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method.

    Science.gov (United States)

    Zhang, Guanglei; Liu, Fei; Liu, Jie; Luo, Jianwen; Xie, Yaoqin; Bai, Jing; Xing, Lei

    2017-01-01

    X-ray luminescence computed tomography (XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. Combining the principles of X-ray excitation of luminescence-based probes and optical signal detection, XLCT naturally fuses functional and anatomical images and provides complementary information for a wide range of applications in biomedical research. In order to improve the data acquisition efficiency of previously developed narrow-beam XLCT, a cone beam XLCT (CB-XLCT) mode is adopted here to take advantage of the useful geometric features of cone beam excitation. Practically, a major hurdle in using cone beam X-ray for XLCT is that the inverse problem here is seriously ill-conditioned, hindering us to achieve good image quality. In this paper, we propose a novel Bayesian method to tackle the bottleneck in CB-XLCT reconstruction. The method utilizes a local regularization strategy based on Gaussian Markov random field to mitigate the ill-conditioness of CB-XLCT. An alternating optimization scheme is then used to automatically calculate all the unknown hyperparameters while an iterative coordinate descent algorithm is adopted to reconstruct the image with a voxel-based closed-form solution. Results of numerical simulations and mouse experiments show that the self-adaptive Bayesian method significantly improves the CB-XLCT image quality as compared with conventional methods.

  1. A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory.

    Science.gov (United States)

    Jiang, Wen; Cao, Ying; Yang, Lin; He, Zichang

    2017-08-28

    Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven't taken into account the processing of uncertain information. Therefore, this paper proposes a time-space domain information fusion method based on Dempster-Shafer evidence theory, which has the ability to deal with uncertain information in the process of specific emitter identification. In this paper, radars will generate a group of evidence respectively based on the information they obtained, and our main task is to fuse the multiple groups of evidence to get a reasonable result. Within the framework of recursive centralized fusion model, the proposed method incorporates a correlation coefficient, which measures the relevance between evidence and a quantum mechanical approach, which is based on the parameters of radar itself. The simulation results of an illustrative example demonstrate that the proposed method can effectively deal with uncertain information and get a reasonable recognition result.

  2. Proposal optimization in nuclear accident emergency decision based on IAHP

    International Nuclear Information System (INIS)

    Xin Jing

    2007-01-01

    On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

  3. Multiple Signal Classification Algorithm Based Electric Dipole Source Localization Method in an Underwater Environment

    Directory of Open Access Journals (Sweden)

    Yidong Xu

    2017-10-01

    Full Text Available A novel localization method based on multiple signal classification (MUSIC algorithm is proposed for positioning an electric dipole source in a confined underwater environment by using electric dipole-receiving antenna array. In this method, the boundary element method (BEM is introduced to analyze the boundary of the confined region by use of a matrix equation. The voltage of each dipole pair is used as spatial-temporal localization data, and it does not need to obtain the field component in each direction compared with the conventional fields based localization method, which can be easily implemented in practical engineering applications. Then, a global-multiple region-conjugate gradient (CG hybrid search method is used to reduce the computation burden and to improve the operation speed. Two localization simulation models and a physical experiment are conducted. Both the simulation results and physical experiment result provide accurate positioning performance, with the help to verify the effectiveness of the proposed localization method in underwater environments.

  4. Proposal of flexible atomic and molecular process management for Monte Carlo impurity transport code based on object oriented method

    International Nuclear Information System (INIS)

    Asano, K.; Ohno, N.; Takamura, S.

    2001-01-01

    Monte Carlo simulation code on impurity transport has been developed by several groups to be utilized mainly for fusion related edge plasmas. State of impurity particle is determined by atomic and molecular processes such as ionization, charge exchange in plasma. A lot of atomic and molecular processes have been considered because the edge plasma has not only impurity atoms, but also impurity molecules mainly related to chemical erosion of carbon materials, and their cross sections have been given experimentally and theoretically. We need to reveal which process is essential in a given edge plasma condition. Monte Carlo simulation code, which takes such various atomic and molecular processes into account, is necessary to investigate the behavior of impurity particle in plasmas. Usually, the impurity transport simulation code has been intended for some specific atomic and molecular processes so that the introduction of a new process forces complicated programming work. In order to evaluate various proposed atomic and molecular processes, a flexible management of atomic and molecular reaction should be established. We have developed the impurity transport simulation code based on object-oriented method. By employing object-oriented programming, we can handle each particle as 'object', which enfolds data and procedure function itself. A user (notice, not programmer) can define property of each particle species and the related atomic and molecular processes and then each 'object' is defined by analyzing this information. According to the relation among plasma particle species, objects are connected with each other and change their state by themselves. Dynamic allocation of these objects to program memory is employed to adapt for arbitrary number of species and atomic/molecular reactions. Thus we can treat arbitrary species and process starting from, for instance, methane and acetylene. Such a software procedure would be useful also for industrial application plasmas

  5. KINECT-BASED REAL-TIME RGB-D IMAGE FUSION METHOD

    Directory of Open Access Journals (Sweden)

    W. Guo

    2012-07-01

    Full Text Available 3D reconstruction of indoor environments based on vision has been developed vigorously. However, the algorithm's complexity and requirements of professional knowledge make it restricted in practical application. With the proposition of the concept of Volunteered Geographic Information (VGI, the traditional method is no longer suitable for VGI. So in this work we utilize consumer depth cameras – Kinect to enable non-expert users to reconstruct 3D model of indoor environment with RGB-D data. Considering the possibility of camera tracking failure we propose a method to perform automatic relocalization.

  6. DNS Tunneling Detection Method Based on Multilabel Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Ahmed Almusawi

    2018-01-01

    Full Text Available DNS tunneling is a method used by malicious users who intend to bypass the firewall to send or receive commands and data. This has a significant impact on revealing or releasing classified information. Several researchers have examined the use of machine learning in terms of detecting DNS tunneling. However, these studies have treated the problem of DNS tunneling as a binary classification where the class label is either legitimate or tunnel. In fact, there are different types of DNS tunneling such as FTP-DNS tunneling, HTTP-DNS tunneling, HTTPS-DNS tunneling, and POP3-DNS tunneling. Therefore, there is a vital demand to not only detect the DNS tunneling but rather classify such tunnel. This study aims to propose a multilabel support vector machine in order to detect and classify the DNS tunneling. The proposed method has been evaluated using a benchmark dataset that contains numerous DNS queries and is compared with a multilabel Bayesian classifier based on the number of corrected classified DNS tunneling instances. Experimental results demonstrate the efficacy of the proposed SVM classification method by obtaining an f-measure of 0.80.

  7. An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

    Science.gov (United States)

    Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

    2013-05-01

    Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

  8. Evaluation of proxy-based millennial reconstruction methods

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Terry C.K.; Tsao, Min [University of Victoria, Department of Mathematics and Statistics, Victoria, BC (Canada); Zwiers, Francis W. [Environment Canada, Climate Research Division, Toronto, ON (Canada)

    2008-08-15

    A range of existing statistical approaches for reconstructing historical temperature variations from proxy data are compared using both climate model data and real-world paleoclimate proxy data. We also propose a new method for reconstruction that is based on a state-space time series model and Kalman filter algorithm. The state-space modelling approach and the recently developed RegEM method generally perform better than their competitors when reconstructing interannual variations in Northern Hemispheric mean surface air temperature. On the other hand, a variety of methods are seen to perform well when reconstructing surface air temperature variability on decadal time scales. An advantage of the new method is that it can incorporate additional, non-temperature, information into the reconstruction, such as the estimated response to external forcing, thereby permitting a simultaneous reconstruction and detection analysis as well as future projection. An application of these extensions is also demonstrated in the paper. (orig.)

  9. A novel collaborative representation and SCAD based classification method for fibrosis and inflammatory activity analysis of chronic hepatitis C

    Science.gov (United States)

    Cai, Jiaxin; Chen, Tingting; Li, Yan; Zhu, Nenghui; Qiu, Xuan

    2018-03-01

    In order to analysis the fibrosis stage and inflammatory activity grade of chronic hepatitis C, a novel classification method based on collaborative representation (CR) with smoothly clipped absolute deviation penalty (SCAD) penalty term, called CR-SCAD classifier, is proposed for pattern recognition. After that, an auto-grading system based on CR-SCAD classifier is introduced for the prediction of fibrosis stage and inflammatory activity grade of chronic hepatitis C. The proposed method has been tested on 123 clinical cases of chronic hepatitis C based on serological indexes. Experimental results show that the performance of the proposed method outperforms the state-of-the-art baselines for the classification of fibrosis stage and inflammatory activity grade of chronic hepatitis C.

  10. Scaling Mode Shapes in Output-Only Structure by a Mass-Change-Based Method

    Directory of Open Access Journals (Sweden)

    Liangliang Yu

    2017-01-01

    Full Text Available A mass-change-based method based on output-only data for the rescaling of mode shapes in operational modal analysis (OMA is introduced. The mass distribution matrix, which is defined as a diagonal matrix whose diagonal elements represent the ratios among the diagonal elements of the mass matrix, is calculated using the unscaled mode shapes. Based on the theory of null space, the mass distribution vector or mass distribution matrix is obtained. A small mass with calibrated weight is added to a certain location of the structure, and then the mass distribution vector of the modified structure is estimated. The mass matrix is identified according to the difference of the mass distribution vectors between the original and modified structures. Additionally, the universal set of modes is unnecessary when calculating the mass distribution matrix, indicating that modal truncation is allowed in the proposed method. The mass-scaled mode shapes estimated in OMA according to the proposed method are compared with those obtained by experimental modal analysis. A simulation is employed to validate the feasibility of the method. Finally, the method is tested on output-only data from an experiment on a five-storey structure, and the results confirm the effectiveness of the method.

  11. Research on Intelligent Avoidance Method of Shipwreck Based on Bigdata Analysis

    Directory of Open Access Journals (Sweden)

    Li Wei

    2017-11-01

    Full Text Available In order to solve the problem that current avoidance method of shipwreck has the problem of low success rate of avoidance, this paper proposes a method of intelligent avoidance of shipwreck based on big data analysis. Firstly,our method used big data analysis to calculate the safe distance of approach of ship under the head-on situation, the crossing situation and the overtaking situation.On this basis, by calculating the risk-degree of collision of ships,our research determined the degree of immediate danger of ships.Finally, we calculated the three kinds of evaluation function of ship navigation, and used genetic algorithm to realize the intelligent avoidance of shipwreck.Experimental result shows that compared the proposed method with the traditional method in two in a recent meeting when the distance to closest point of approach between two ships is 0.13nmile, they can effectively evade.The success rate of avoidance is high.

  12. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lijuan Duan

    2017-01-01

    Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

  13. Visual-Simulation-Based Personalized Garment Block Design Method for Physically Disabled People with Scoliosis (PDPS

    Directory of Open Access Journals (Sweden)

    Hong Yan

    2018-03-01

    Full Text Available This research presented a novel method using 3D simulation methods to design customized garments for physically disabled people with scoliosis (PDPS. The proposed method is based on the virtual human model created from 3D scanning, permitting to simulate the consumer’s morphological shape with atypical physical deformations. Next, customized 2D and 3D virtual garment prototyping tools will be used to create products through interactions. The proposed 3D garment design method is based on the concept of knowledge-based design, using the design knowledge and process already applied to normal body shapes successfully. The characters of the PDPS and the relationship between human body and garment are considered in the prototyping process. As a visualized collaborative design process, the communication between designer and consumer is ensured, permitting to adapt the finished product to disabled people afflicted with severe scoliosis.

  14. Real reproduction and evaluation of color based on BRDF method

    Science.gov (United States)

    Qin, Feng; Yang, Weiping; Yang, Jia; Li, Hongning; Luo, Yanlin; Long, Hongli

    2013-12-01

    It is difficult to reproduce the original color of targets really in different illuminating environment using the traditional methods. So a function which can reconstruct the characteristics of reflection about every point on the surface of target is required urgently to improve the authenticity of color reproduction, which known as the Bidirectional Reflectance Distribution Function(BRDF). A method of color reproduction based on the BRDF measurement is introduced in this paper. Radiometry is combined with the colorimetric theories to measure the irradiance and radiance of GretagMacbeth 24 ColorChecker by using PR-715 Radiation Spectrophotometer of PHOTO RESEARCH, Inc, USA. The BRDF and BRF (Bidirectional Reflectance Factor) values of every color piece corresponding to the reference area are calculated according to irradiance and radiance, thus color tristimulus values of 24 ColorChecker are reconstructed. The results reconstructed by BRDF method are compared with values calculated by the reflectance using PR-715, at last, the chromaticity coordinates in color space and color difference between each other are analyzed. The experimental result shows average color difference and sample standard deviation between the method proposed in this paper and traditional reconstruction method depended on reflectance are 2.567 and 1.3049 respectively. The conclusion indicates that the method of color reproduction based on BRDF has the more obvious advantages to describe the color information of object than the reflectance in hemisphere space through the theoretical and experimental analysis. This method proposed in this paper is effective and feasible during the research of reproducing the chromaticity.

  15. An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

    Science.gov (United States)

    Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

    2018-01-01

    In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

  16. Deviation-based spam-filtering method via stochastic approach

    Science.gov (United States)

    Lee, Daekyung; Lee, Mi Jin; Kim, Beom Jun

    2018-03-01

    In the presence of a huge number of possible purchase choices, ranks or ratings of items by others often play very important roles for a buyer to make a final purchase decision. Perfectly objective rating is an impossible task to achieve, and we often use an average rating built on how previous buyers estimated the quality of the product. The problem of using a simple average rating is that it can easily be polluted by careless users whose evaluation of products cannot be trusted, and by malicious spammers who try to bias the rating result on purpose. In this letter we suggest how trustworthiness of individual users can be systematically and quantitatively reflected to build a more reliable rating system. We compute the suitably defined reliability of each user based on the user's rating pattern for all products she evaluated. We call our proposed method as the deviation-based ranking, since the statistical significance of each user's rating pattern with respect to the average rating pattern is the key ingredient. We find that our deviation-based ranking method outperforms existing methods in filtering out careless random evaluators as well as malicious spammers.

  17. An Intelligent Method for Structural Reliability Analysis Based on Response Surface

    Institute of Scientific and Technical Information of China (English)

    桂劲松; 刘红; 康海贵

    2004-01-01

    As water depth increases, the structural safety and reliability of a system become more and more important and challenging. Therefore, the structural reliability method must be applied in ocean engineering design such as offshore platform design. If the performance function is known in structural reliability analysis, the first-order second-moment method is often used. If the performance function could not be definitely expressed, the response surface method is always used because it has a very clear train of thought and simple programming. However, the traditional response surface method fits the response surface of quadratic polynomials where the problem of accuracy could not be solved, because the true limit state surface can be fitted well only in the area near the checking point. In this paper, an intelligent computing method based on the whole response surface is proposed, which can be used for the situation where the performance function could not be definitely expressed in structural reliability analysis. In this method, a response surface of the fuzzy neural network for the whole area should be constructed first, and then the structural reliability can be calculated by the genetic algorithm. In the proposed method, all the sample points for the training network come from the whole area, so the true limit state surface in the whole area can be fitted. Through calculational examples and comparative analysis, it can be known that the proposed method is much better than the traditional response surface method of quadratic polynomials, because, the amount of calculation of finite element analysis is largely reduced, the accuracy of calculation is improved,and the true limit state surface can be fitted very well in the whole area. So, the method proposed in this paper is suitable for engineering application.

  18. Method for Car in Dangerous Action Detection by Means of Wavelet Multi Resolution Analysis Based on Appropriate Support Length of Base Function

    OpenAIRE

    Kohei Arai; Tomoko Nishikawa

    2013-01-01

    Multi-Resolution Analysis: MRA based on the mother wavelet function with which support length differs from the image of the automobile rear under run is performed, and the run characteristic of a car is searched for. Speed, deflection, etc. are analyzed and the method of detecting vehicles with high accident danger is proposed. The experimental results show that vehicles in a dangerous action can be detected by the proposed method.

  19. An improved gravity compensation method for high-precision free-INS based on MEC–BP–AdaBoost

    International Nuclear Information System (INIS)

    Zhou, Xiao; Yang, Gongliu; Wang, Jing; Li, Jing

    2016-01-01

    In recent years, with the rapid improvement of inertial sensors (accelerometers and gyroscopes), gravity compensation has become more important for improving navigation accuracy in inertial navigation systems (INS), especially for high-precision INS. This paper proposes a mind evolutionary computation (MEC) back propagation (BP) AdaBoost algorithm neural-network-based gravity compensation method that estimates the gravity disturbance on the track based on measured gravity data. A MEC–BP–AdaBoost network-based gravity compensation algorithm used in the training process to establish the prediction model takes the carrier position (longitude and latitude) provided by INS as the input data and the gravity disturbance as the output data, and then compensates the obtained gravity disturbance into the INS’s error equations to restrain the position error propagation. The MEC–BP–AdaBoost algorithm can not only effectively avoid BP neural networks being trapped in local extrema, but also perfectly solve the nonlinearity between the input and output data that cannot be solved by traditional interpolation methods, such as least-square collocation (LSC) interpolation. The accuracy and feasibility of the proposed interpolation method are verified through numerical tests. A comparison of several other compensation methods applied in field experiments, including LSC interpolation and traditional BP interpolation, highlights the superior performance of the proposed method. The field experiment results show that the maximum value of the position error can reduce by 28% with the proposed gravity compensation method. (paper)

  20. A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

    Science.gov (United States)

    Feng, Shou; Fu, Ping; Zheng, Wenbin

    2018-03-01

    Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

  1. MCDM based evaluation and ranking of commercial off-the-shelf using fuzzy based matrix method

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2017-04-01

    Full Text Available In today’s scenario, software has become an essential component in all kinds of systems. The size and the complexity of the software increases with a corresponding increase in its functionality, hence leads to the development of the modular software systems. Software developers emphasize on the concept of component based software engineering (CBSE for the development of modular software systems. The CBSE concept consists of dividing the software into a number of modules; selecting Commercial Off-the-Shelf (COTS for each module; and finally integrating the modules to develop the final software system. The selection of COTS for any module plays a vital role in software development. To address the problem of selection of COTS, a framework for ranking and selection of various COTS components for any software system based on expert opinion elicitation and fuzzy-based matrix methodology is proposed in this research paper. The selection problem is modeled as a multi-criteria decision making (MCDM problem. The evaluation criteria are identified through extensive literature study and the COTS components are ranked based on these identified and selected evaluation criteria using the proposed methods according to the value of a permanent function of their criteria matrices. The methodology is explained through an example and is validated by comparing with an existing method.

  2. Methods for Engineering Enterprise Management Based on the Inter-factor Productive-Economic Relations

    Directory of Open Access Journals (Sweden)

    O. A. Naydis

    2015-01-01

    Full Text Available The article analyzes the current state of engineering enterprises in the Russian Federation. It conducts a review and analysis of existing methods for business management using indicators to characterize enterprise activities by means of the scalars, functional dependencies of one factor value on the other (function one, wherein the magnitude of one factor value corresponds to a single magnitude of the other value - a dependent factor, as well as by means of data tables, and, as an example, by balance list and articulation statement used in accounting. The paper gives statements of need for taking into account the mutual influences and system interrelation of factors diversity and for special methods of their identification. The article is aimed at development of methods for business management of engineering enterprises taking into account a variety of factors and their interdependencies. The relevance of the issue stems from the fact that the analysis of existing methods of business management has shown that it is impossible to have the requested information about a considerable number of productive-economic factors in their system-based interrelation. There is a proposal for the management objects wherein multiple factors and their interactions are taken into consideration to be called inter-factor productive-economic relations (IPER. The paper presents the IPER-based structure of the business management system. It describes a method to identify controlled productive-economic factors and provides allocation and justification of the significant ones for the IPER control. Described methods of business management are distinguished by a large amount of control information, and data form rather complex structures. Therefore, it is proposed to use them in automatic control systems. The paper describes principles of information support for business management through binding IPER to organizational structures of the enterprise. It offers an

  3. Improved Real-time Denoising Method Based on Lifting Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Liu Zhaohua

    2014-06-01

    Full Text Available Signal denoising can not only enhance the signal to noise ratio (SNR but also reduce the effect of noise. In order to satisfy the requirements of real-time signal denoising, an improved semisoft shrinkage real-time denoising method based on lifting wavelet transform was proposed. The moving data window technology realizes the real-time wavelet denoising, which employs wavelet transform based on lifting scheme to reduce computational complexity. Also hyperbolic threshold function and recursive threshold computing can ensure the dynamic characteristics of the system, in addition, it can improve the real-time calculating efficiency as well. The simulation results show that the semisoft shrinkage real-time denoising method has quite a good performance in comparison to the traditional methods, namely soft-thresholding and hard-thresholding. Therefore, this method can solve more practical engineering problems.

  4. Resistance Torque Based Variable Duty-Cycle Control Method for a Stage II Compressor

    Science.gov (United States)

    Zhong, Meipeng; Zheng, Shuiying

    2017-07-01

    The resistance torque of a piston stage II compressor generates strenuous fluctuations in a rotational period, and this can lead to negative influences on the working performance of the compressor. To restrain the strenuous fluctuations in the piston stage II compressor, a variable duty-cycle control method based on the resistance torque is proposed. A dynamic model of a stage II compressor is set up, and the resistance torque and other characteristic parameters are acquired as the control targets. Then, a variable duty-cycle control method is applied to track the resistance torque, thereby improving the working performance of the compressor. Simulated results show that the compressor, driven by the proposed method, requires lower current, while the rotating speed and the output torque remain comparable to the traditional variable-frequency control methods. A variable duty-cycle control system is developed, and the experimental results prove that the proposed method can help reduce the specific power, input power, and working noise of the compressor to 0.97 kW·m-3·min-1, 0.09 kW and 3.10 dB, respectively, under the same conditions of discharge pressure of 2.00 MPa and a discharge volume of 0.095 m3/min. The proposed variable duty-cycle control method tracks the resistance torque dynamically, and improves the working performance of a Stage II Compressor. The proposed variable duty-cycle control method can be applied to other compressors, and can provide theoretical guidance for the compressor.

  5. Kernel based methods for accelerated failure time model with ultra-high dimensional data

    Directory of Open Access Journals (Sweden)

    Jiang Feng

    2010-12-01

    Full Text Available Abstract Background Most genomic data have ultra-high dimensions with more than 10,000 genes (probes. Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n ≪ m (the number of genes, directly identifying a small subset of genes from ultra-high (m > 10, 000 dimensional data is time-consuming and not computationally efficient. In current microarray analysis, what people really do is select a couple of thousands (or hundreds of genes using univariate analysis or statistical tests, and then apply the LASSO-type penalty to further reduce the number of disease associated genes. This two-step procedure may introduce bias and inaccuracy and lead us to miss biologically important genes. Results The accelerated failure time (AFT model is a linear regression model and a useful alternative to the Cox model for survival analysis. In this paper, we propose a nonlinear kernel based AFT model and an efficient variable selection method with adaptive kernel ridge regression. Our proposed variable selection method is based on the kernel matrix and dual problem with a much smaller n × n matrix. It is very efficient when the number of unknown variables (genes is much larger than the number of samples. Moreover, the primal variables are explicitly updated and the sparsity in the solution is exploited. Conclusions Our proposed methods can simultaneously identify survival associated prognostic factors and predict survival outcomes with ultra-high dimensional genomic data. We have demonstrated the performance of our methods with both simulation and real data. The proposed method performs superbly with limited computational studies.

  6. A Project Strategic Index proposal for portfolio selection in electrical company based on the Analytic Network Process

    Energy Technology Data Exchange (ETDEWEB)

    Smith-Perera, Aida [Universidad Metropolitana de Caracas, Departamento de Gestion Tecnologica, Caracas 1071, Edo Miranda (Venezuela); Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual [Universidad Politecnica de Valencia, Departamento de Proyectos de Ingenieria, Camino de vera s/n 46022 Valencia (Spain)

    2010-08-15

    In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)

  7. A Project Strategic Index proposal for portfolio selection in electrical company based on the Analytic Network Process

    International Nuclear Information System (INIS)

    Smith-Perera, Aida; Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual

    2010-01-01

    In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)

  8. Ionospheric forecasting model using fuzzy logic-based gradient descent method

    Directory of Open Access Journals (Sweden)

    D. Venkata Ratnam

    2017-09-01

    Full Text Available Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC. Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E. It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements.

  9. Reconstruction of Banknote Fragments Based on Keypoint Matching Method.

    Science.gov (United States)

    Gwo, Chih-Ying; Wei, Chia-Hung; Li, Yue; Chiu, Nan-Hsing

    2015-07-01

    Banknotes may be shredded by a scrap machine, ripped up by hand, or damaged in accidents. This study proposes an image registration method for reconstruction of multiple sheets of banknotes. The proposed method first constructs different scale spaces to identify keypoints in the underlying banknote fragments. Next, the features of those keypoints are extracted to represent their local patterns around keypoints. Then, similarity is computed to find the keypoint pairs between the fragment and the reference banknote. The banknote fragments can determine the coordinate and amend the orientation. Finally, an assembly strategy is proposed to piece multiple sheets of banknote fragments together. Experimental results show that the proposed method causes, on average, a deviation of 0.12457 ± 0.12810° for each fragment while the SIFT method deviates 1.16893 ± 2.35254° on average. The proposed method not only reconstructs the banknotes but also decreases the computing cost. Furthermore, the proposed method can estimate relatively precisely the orientation of the banknote fragments to assemble. © 2015 American Academy of Forensic Sciences.

  10. Interference coupling analysis based on a hybrid method: application to a radio telescope system

    Science.gov (United States)

    Xu, Qing-Lin; Qiu, Yang; Tian, Jin; Liu, Qi

    2018-02-01

    Working in a way that passively receives electromagnetic radiation from a celestial body, a radio telescope can be easily disturbed by external radio frequency interference as well as electromagnetic interference generated by electric and electronic components operating at the telescope site. A quantitative analysis of these interferences must be taken into account carefully for further electromagnetic protection of the radio telescope. In this paper, based on electromagnetic topology theory, a hybrid method that combines the Baum-Liu-Tesche (BLT) equation and transfer function is proposed. In this method, the coupling path of the radio telescope is divided into strong coupling and weak coupling sub-paths, and the coupling intensity criterion is proposed by analyzing the conditions in which the BLT equation simplifies to a transfer function. According to the coupling intensity criterion, the topological model of a typical radio telescope system is established. The proposed method is used to solve the interference response of the radio telescope system by analyzing subsystems with different coupling modes separately and then integrating the responses of the subsystems as the response of the entire system. The validity of the proposed method is verified numerically. The results indicate that the proposed method, compared with the direct solving method, reduces the difficulty and improves the efficiency of interference prediction.

  11. Vehicle Speed Estimation and Forecasting Methods Based on Cellular Floating Vehicle Data

    Directory of Open Access Journals (Sweden)

    Wei-Kuang Lai

    2016-02-01

    Full Text Available Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD are proposed to analyze the signals (e.g., handovers (HOs, call arrivals (CAs, normal location updates (NLUs and periodic location updates (PLUs from cellular networks. For traffic information estimation, analytic models are proposed to estimate the traffic flow in accordance with the amounts of HOs and NLUs and to estimate the traffic density in accordance with the amounts of CAs and PLUs. Then, the vehicle speeds can be estimated in accordance with the estimated traffic flows and estimated traffic densities. For vehicle speed forecasting, a back-propagation neural network algorithm is considered to predict the future vehicle speed in accordance with the current traffic information (i.e., the estimated vehicle speeds from CFVD. In the experimental environment, this study adopted the practical traffic information (i.e., traffic flow and vehicle speed from Taiwan Area National Freeway Bureau as the input characteristics of the traffic simulation program and referred to the mobile station (MS communication behaviors from Chunghwa Telecom to simulate the traffic information and communication records. The experimental results illustrated that the average accuracy of the vehicle speed forecasting method is 95.72%. Therefore, the proposed methods based on CFVD are suitable for an intelligent transportation system.

  12. A kriging metamodel-assisted robust optimization method based on a reverse model

    Science.gov (United States)

    Zhou, Hui; Zhou, Qi; Liu, Congwei; Zhou, Taotao

    2018-02-01

    The goal of robust optimization methods is to obtain a solution that is both optimum and relatively insensitive to uncertainty factors. Most existing robust optimization approaches use outer-inner nested optimization structures where a large amount of computational effort is required because the robustness of each candidate solution delivered from the outer level should be evaluated in the inner level. In this article, a kriging metamodel-assisted robust optimization method based on a reverse model (K-RMRO) is first proposed, in which the nested optimization structure is reduced into a single-loop optimization structure to ease the computational burden. Ignoring the interpolation uncertainties from kriging, K-RMRO may yield non-robust optima. Hence, an improved kriging-assisted robust optimization method based on a reverse model (IK-RMRO) is presented to take the interpolation uncertainty of kriging metamodel into consideration. In IK-RMRO, an objective switching criterion is introduced to determine whether the inner level robust optimization or the kriging metamodel replacement should be used to evaluate the robustness of design alternatives. The proposed criterion is developed according to whether or not the robust status of the individual can be changed because of the interpolation uncertainties from the kriging metamodel. Numerical and engineering cases are used to demonstrate the applicability and efficiency of the proposed approach.

  13. Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood

    NARCIS (Netherlands)

    Asadi, A.R.; Roos, C.

    2015-01-01

    In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author.

  14. Real-time 3D imaging methods using 2D phased arrays based on synthetic focusing techniques.

    Science.gov (United States)

    Kim, Jung-Jun; Song, Tai-Kyong

    2008-07-01

    A fast 3D ultrasound imaging technique using a 2D phased array transducer based on the synthetic focusing method for nondestructive testing or medical imaging is proposed. In the proposed method, each column of a 2D array is fired successively to produce transverse fan beams focused at a fixed depth along a given longitudinal direction and the resulting pulse echoes are received at all elements of a 2D array used. After firing all column arrays, a frame of high-resolution image along a given longitudinal direction is obtained with dynamic focusing employed in the longitudinal direction on receive and in the transverse direction on both transmit and receive. The volume rate of the proposed method can be increased much higher than that of the conventional 2D array imaging by employing an efficient sparse array technique. A simple modification to the proposed method can further increase the volume scan rate significantly. The proposed methods are verified through computer simulations.

  15. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  16. A Method for Driving Route Predictions Based on Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available We present a driving route prediction method that is based on Hidden Markov Model (HMM. This method can accurately predict a vehicle’s entire route as early in a trip’s lifetime as possible without inputting origins and destinations beforehand. Firstly, we propose the route recommendation system architecture, where route predictions play important role in the system. Secondly, we define a road network model, normalize each of driving routes in the rectangular coordinate system, and build the HMM to make preparation for route predictions using a method of training set extension based on K-means++ and the add-one (Laplace smoothing technique. Thirdly, we present the route prediction algorithm. Finally, the experimental results of the effectiveness of the route predictions that is based on HMM are shown.

  17. Location Privacy Protection Based on Improved K-Value Method in Augmented Reality on Mobile Devices

    Directory of Open Access Journals (Sweden)

    Chunyong Yin

    2017-01-01

    Full Text Available With the development of Augmented Reality technology, the application of location based service (LBS is more and more popular, which provides enormous convenience to people’s life. User location information could be obtained at anytime and anywhere. So user location privacy security suffers huge threats. Therefore, it is crucial to pay attention to location privacy protection in LBS. Based on the architecture of the trusted third party (TTP, we analyzed the advantages and shortages of existing location privacy protection methods in LBS on mobile terminal. Then we proposed the improved K-value location privacy protection method according to privacy level, which combines k-anonymity method with pseudonym method. Through the simulation experiment, the results show that this improved method can anonymize all service requests effectively. In addition to the experiment of execution time, it demonstrated that our proposed method can realize the location privacy protection more efficiently.

  18. Variable aperture-based ptychographical iterative engine method.

    Science.gov (United States)

    Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

    2018-02-01

    A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  19. Fault diagnosis method for nuclear power plants based on neural networks and voting fusion

    International Nuclear Information System (INIS)

    Zhou Gang; Ge Shengqi; Yang Li

    2010-01-01

    A new fault diagnosis method based on multiple neural networks (ANNs) and voting fusion for nuclear power plants (NPPs) was proposed in view of the shortcoming of single neural network fault diagnosis method. In this method, multiple neural networks that the types of neural networks were different were trained for the fault diagnosis of NPP. The operation parameters of NPP, which have important affect on the safety of NPP, were selected as the input variable of neural networks. The output of neural networks is fault patterns of NPP. The last results of diagnosis for NPP were obtained by fusing the diagnosing results of different neural networks by voting fusion. The typical operation patterns of NPP were diagnosed to demonstrate the effect of the proposed method. The results show that employing the proposed diagnosing method can improve the precision and reliability of fault diagnosis results of NPPs. (authors)

  20. Structural reliability calculation method based on the dual neural network and direct integration method.

    Science.gov (United States)

    Li, Haibin; He, Yun; Nie, Xiaobo

    2018-01-01

    Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

  1. A simulation training evaluation method for distribution network fault based on radar chart

    Directory of Open Access Journals (Sweden)

    Yuhang Xu

    2018-01-01

    Full Text Available In order to solve the problem of automatic evaluation of dispatcher fault simulation training in distribution network, a simulation training evaluation method based on radar chart for distribution network fault is proposed. The fault handling information matrix is established to record the dispatcher fault handling operation sequence and operation information. The four situations of the dispatcher fault isolation operation are analyzed. The fault handling anti-misoperation rule set is established to describe the rules prohibiting dispatcher operation. Based on the idea of artificial intelligence reasoning, the feasibility of dispatcher fault handling is described by the feasibility index. The relevant factors and evaluation methods are discussed from the three aspects of the fault handling result feasibility, the anti-misoperation correctness and the operation process conciseness. The detailed calculation formula is given. Combining the independence and correlation between the three evaluation angles, a comprehensive evaluation method of distribution network fault simulation training based on radar chart is proposed. The method can comprehensively reflect the fault handling process of dispatchers, and comprehensively evaluate the fault handling process from various angles, which has good practical value.

  2. Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

    Directory of Open Access Journals (Sweden)

    Wen-Yeau Chang

    2013-09-01

    Full Text Available High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO based hybrid forecasting method for short-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network, and the radial basis function (RBF neural network. The EPSO algorithm is employed to optimize the weight coefficients in the hybrid forecasting method. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a wind energy conversion system (WECS installed on the Taichung coast of Taiwan. Comparisons of forecasting performance are made with the individual forecasting methods. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.

  3. Nondestructive assessment of timber bridges using a vibration-based method

    Science.gov (United States)

    Xiping Wang; James P. Wacker; Robert J. Ross; Brian K. Brashaw

    2005-01-01

    This paper describes an effort to develop a global dynamic testing technique for evaluating the overall stiffness of timber bridge superstructures. A forced vibration method was used to measure the natural frequency of single-span timber bridges in the laboratory and field. An analytical model based on simple beam theory was proposed to represent the relationship...

  4. Proposed Brookhaven accelerator-based neutron generator

    International Nuclear Information System (INIS)

    Grand, P.; Batchelor, K.; Chasman, R.; Rheaume, R.

    1976-01-01

    The d-Li Neutron Source concept, which includes a high-current dueteron linac, is an outgrowth of attempts made to use the BNL, 200-MeV proton linac BLIP facility to do radiation damage studies. It included a 100 mA, 30-MeV deuteron linear accelerator and a fast-flowing liquid lithium jet as the target. The latest design is not very different, except that the current is now 200 mA and the linac energy has been raised to 35 MeV. Both parameters, were changed to optimize the effectiveness of the facility with respect to flux, experimental volume and match to 14 MeV neutron-radiation-damage effects. The proposed Brookhaven Accelerator-based Neutron Generator is described with particular emphasis on the linear accelerator. The proposed facility is a practical and efficient way of producing the intense, high energy neutron beams needed for CTR material studies. The accelerator and liquid-metal technologies are well proven, state-of-the-art technologies. The fact that no new technology is required guarantees the possibility of meeting construction schedules, and more importantly, guarantees a high level of operational reliability

  5. Improved Taguchi method based contract capacity optimization for industrial consumer with self-owned generating units

    International Nuclear Information System (INIS)

    Yang, Hong-Tzer; Peng, Pai-Chun

    2012-01-01

    Highlights: ► We propose an improved Taguchi method to determine the optimal contract capacities with SOGUs. ► We solve the highly discrete and nonlinear optimization problem for the contract capacities with SOGUs. ► The proposed improved Taguchi method integrates PSO in Taguchi method. ► The customer using the proposed optimization approach may save up to 12.18% of power expenses. ► The improved Taguchi method can also be well applied to the other similar problems. - Abstract: Contract capacity setting for industrial consumer with self-owned generating units (SOGUs) is a highly discrete and nonlinear optimization problem considering expenditure on the electricity from the utility and operation costs of the SOGUs. This paper proposes an improved Taguchi method that combines existing Taguchi method and particle swarm optimization (PSO) algorithm to solve this problem. Taguchi method provides fast converging characteristics in searching the optimal solution through quality analysis in orthogonal matrices. The integrated PSO algorithm generates new solutions in the orthogonal matrices based on the searching experiences during the evolution process to further improve the quality of solution. To verify feasibility of the proposed method, the paper uses the real data obtained from a large optoelectronics factory in Taiwan. In comparison with the existing optimization methods, the proposed improved Taguchi method has superior performance as revealed in the numerical results in terms of the convergence process and the quality of solution obtained.

  6. The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

    Science.gov (United States)

    Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

    2017-05-01

    The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

  7. A method of vehicle license plate recognition based on PCANet and compressive sensing

    Science.gov (United States)

    Ye, Xianyi; Min, Feng

    2018-03-01

    The manual feature extraction of the traditional method for vehicle license plates has no good robustness to change in diversity. And the high feature dimension that is extracted with Principal Component Analysis Network (PCANet) leads to low classification efficiency. For solving these problems, a method of vehicle license plate recognition based on PCANet and compressive sensing is proposed. First, PCANet is used to extract the feature from the images of characters. And then, the sparse measurement matrix which is a very sparse matrix and consistent with Restricted Isometry Property (RIP) condition of the compressed sensing is used to reduce the dimensions of extracted features. Finally, the Support Vector Machine (SVM) is used to train and recognize the features whose dimension has been reduced. Experimental results demonstrate that the proposed method has better performance than Convolutional Neural Network (CNN) in the recognition and time. Compared with no compression sensing, the proposed method has lower feature dimension for the increase of efficiency.

  8. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Directory of Open Access Journals (Sweden)

    Chen Gong-bo

    2013-06-01

    Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

  9. A practical method for extending the biuret assay to protein determination of corn-based products.

    Science.gov (United States)

    Liu, Zelong; Pan, Junhui

    2017-06-01

    A modified biuret method suitable for protein determination of corn-based products was developed by introducing a combination of an alkaline reagent with sodium dodecyl sulfate (reagent A) and heat treatments. The method was tested on seven corn-based samples. The results showed mostly good agreement (P>0.05) as compared to the Kjeldahl values. The proposed method was found to enhance the accuracy of prediction on zein content using bovine serum albumin as standard. Reagent A and sample treatment were proved to effectively improve protein solubilization for the thermally-dried corn-based products, e.g. corn gluten meal. The absorbance was stable for at least 1-h. Moreover, the whole measurement of protein content only needs 15-20min more than the traditional biuret assay, and can be performed in batches. The findings suggest that the proposed method could be a timesaving alternative for routine protein analyses in corn processing factories. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Adaptive and automatic red blood cell counting method based on microscopic hyperspectral imaging technology

    Science.gov (United States)

    Liu, Xi; Zhou, Mei; Qiu, Song; Sun, Li; Liu, Hongying; Li, Qingli; Wang, Yiting

    2017-12-01

    Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu’s method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.

  11. Generating region proposals for histopathological whole slide image retrieval.

    Science.gov (United States)

    Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

    2018-06-01

    Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright

  12. High-precision pose measurement method in wind tunnels based on laser-aided vision technology

    Directory of Open Access Journals (Sweden)

    Liu Wei

    2015-08-01

    Full Text Available The measurement of position and attitude parameters for the isolated target from a high-speed aircraft is a great challenge in the field of wind tunnel simulation technology. In this paper, firstly, an image acquisition method for small high-speed targets with multi-dimensional movement in wind tunnel environment is proposed based on laser-aided vision technology. Combining with the trajectory simulation of the isolated model, the reasonably distributed laser stripes and self-luminous markers are utilized to capture clear images of the object. Then, after image processing, feature extraction, stereo correspondence and reconstruction, three-dimensional information of laser stripes and self-luminous markers are calculated. Besides, a pose solution method based on projected laser stripes and self-luminous markers is proposed. Finally, simulation experiments on measuring the position and attitude of high-speed rolling targets are conducted, as well as accuracy verification experiments. Experimental results indicate that the proposed method is feasible and efficient for measuring the pose parameters of rolling targets in wind tunnels.

  13. A low delay transmission method of multi-channel video based on FPGA

    Science.gov (United States)

    Fu, Weijian; Wei, Baozhi; Li, Xiaobin; Wang, Quan; Hu, Xiaofei

    2018-03-01

    In order to guarantee the fluency of multi-channel video transmission in video monitoring scenarios, we designed a kind of video format conversion method based on FPGA and its DMA scheduling for video data, reduces the overall video transmission delay.In order to sace the time in the conversion process, the parallel ability of FPGA is used to video format conversion. In order to improve the direct memory access (DMA) writing transmission rate of PCIe bus, a DMA scheduling method based on asynchronous command buffer is proposed. The experimental results show that this paper designs a low delay transmission method based on FPGA, which increases the DMA writing transmission rate by 34% compared with the existing method, and then the video overall delay is reduced to 23.6ms.

  14. Novel crystal timing calibration method based on total variation

    Science.gov (United States)

    Yu, Xingjian; Isobe, Takashi; Watanabe, Mitsuo; Liu, Huafeng

    2016-11-01

    A novel crystal timing calibration method based on total variation (TV), abbreviated as ‘TV merge’, has been developed for a high-resolution positron emission tomography (PET) system. The proposed method was developed for a system with a large number of crystals, it can provide timing calibration at the crystal level. In the proposed method, the timing calibration process was formulated as a linear problem. To robustly optimize the timing resolution, a TV constraint was added to the linear equation. Moreover, to solve the computer memory problem associated with the calculation of the timing calibration factors for systems with a large number of crystals, the merge component was used for obtaining the crystal level timing calibration values. Compared with other conventional methods, the data measured from a standard cylindrical phantom filled with a radioisotope solution was sufficient for performing a high-precision crystal-level timing calibration. In this paper, both simulation and experimental studies were performed to demonstrate the effectiveness and robustness of the TV merge method. We compare the timing resolutions of a 22Na point source, which was located in the field of view (FOV) of the brain PET system, with various calibration techniques. After implementing the TV merge method, the timing resolution improved from 3.34 ns at full width at half maximum (FWHM) to 2.31 ns FWHM.

  15. Adjoint-based Mesh Optimization Method: The Development and Application for Nuclear Fuel Analysis

    International Nuclear Information System (INIS)

    Son, Seongmin; Lee, Jeong Ik

    2016-01-01

    In this research, methods for optimizing mesh distribution is proposed. The proposed method uses adjoint base optimization method (adjoint method). The optimized result will be obtained by applying this meshing technique to the existing code input deck and will be compared to the results produced from the uniform meshing method. Numerical solutions are calculated form an in-house 1D Finite Difference Method code while neglecting the axial conduction. The fuel radial node optimization was first performed to match the Fuel Centerline Temperature (FCT) the best. This was followed by optimizing the axial node which the Peak Cladding Temperature (PCT) is matched the best. After obtaining the optimized radial and axial nodes, the nodalization is implemented into the system analysis code and transient analyses were performed to observe the optimum nodalization performance. The developed adjoint-based mesh optimization method in the study is applied to MARS-KS, which is a nuclear system analysis code. Results show that the newly established method yields better results than that of the uniform meshing method from the numerical point of view. It is again stressed that the optimized mesh for the steady state can also give better numerical results even during a transient analysis

  16. Precise positioning method for multi-process connecting based on binocular vision

    Science.gov (United States)

    Liu, Wei; Ding, Lichao; Zhao, Kai; Li, Xiao; Wang, Ling; Jia, Zhenyuan

    2016-01-01

    With the rapid development of aviation and aerospace, the demand for metal coating parts such as antenna reflector, eddy-current sensor and signal transmitter, etc. is more and more urgent. Such parts with varied feature dimensions, complex three-dimensional structures, and high geometric accuracy are generally fabricated by the combination of different manufacturing technology. However, it is difficult to ensure the machining precision because of the connection error between different processing methods. Therefore, a precise positioning method is proposed based on binocular micro stereo vision in this paper. Firstly, a novel and efficient camera calibration method for stereoscopic microscope is presented to solve the problems of narrow view field, small depth of focus and too many nonlinear distortions. Secondly, the extraction algorithms for law curve and free curve are given, and the spatial position relationship between the micro vision system and the machining system is determined accurately. Thirdly, a precise positioning system based on micro stereovision is set up and then embedded in a CNC machining experiment platform. Finally, the verification experiment of the positioning accuracy is conducted and the experimental results indicated that the average errors of the proposed method in the X and Y directions are 2.250 μm and 1.777 μm, respectively.

  17. A Stable-Matching-Based User Linking Method with User Preference Order

    Directory of Open Access Journals (Sweden)

    Xuzhong Wang

    2017-01-01

    Full Text Available With the development of social networks, more and more users choose to use multiple accounts from different networks to meet their needs. Linking a particular user’s multiple accounts not only can improve user’s experience of the net-services such as recommender system, but also plays a significant role in network security. However, multiple accounts of the same user are often not directly linked to each other, and further, the privacy policy provided by the service provider makes it harder to find accounts for a particular user. In this paper, we propose a stable-matching-based method with user preference order for the problem of low accuracy of user linking in cross-media sparse data. Different from the traditional way which just calculates the similarity of accounts, we take full account of the mutual influence among multiple accounts by regarding different networks as bilateral (multilateral market and user linking as a stable matching problem in such a market. Based on the combination of Game-Theoretic Machine Learning and Pairwise, a novel user linking method has been proposed. The experiment shows that our method has a 21.6% improvement in accuracy compared with the traditional linking method and a further increase of about 7.8% after adding the prior knowledge.

  18. Proposed method for reconstructing velocity profiles using a multi-electrode electromagnetic flow meter

    International Nuclear Information System (INIS)

    Kollár, László E; Lucas, Gary P; Zhang, Zhichao

    2014-01-01

    An analytical method is developed for the reconstruction of velocity profiles using measured potential distributions obtained around the boundary of a multi-electrode electromagnetic flow meter (EMFM). The method is based on the discrete Fourier transform (DFT), and is implemented in Matlab. The method assumes the velocity profile in a section of a pipe as a superposition of polynomials up to sixth order. Each polynomial component is defined along a specific direction in the plane of the pipe section. For a potential distribution obtained in a uniform magnetic field, this direction is not unique for quadratic and higher-order components; thus, multiple possible solutions exist for the reconstructed velocity profile. A procedure for choosing the optimum velocity profile is proposed. It is applicable for single-phase or two-phase flows, and requires measurement of the potential distribution in a non-uniform magnetic field. The potential distribution in this non-uniform magnetic field is also calculated for the possible solutions using weight values. Then, the velocity profile with the calculated potential distribution which is closest to the measured one provides the optimum solution. The reliability of the method is first demonstrated by reconstructing an artificial velocity profile defined by polynomial functions. Next, velocity profiles in different two-phase flows, based on results from the literature, are used to define the input velocity fields. In all cases, COMSOL Multiphysics is used to model the physical specifications of the EMFM and to simulate the measurements; thus, COMSOL simulations produce the potential distributions on the internal circumference of the flow pipe. These potential distributions serve as inputs for the analytical method. The reconstructed velocity profiles show satisfactory agreement with the input velocity profiles. The method described in this paper is most suitable for stratified flows and is not applicable to axisymmetric flows in

  19. Optimal plot size in the evaluation of papaya scions: proposal and comparison of methods

    Directory of Open Access Journals (Sweden)

    Humberto Felipe Celanti

    Full Text Available ABSTRACT Evaluating the quality of scions is extremely important and it can be done by characteristics of shoots and roots. This experiment evaluated height of the aerial part, stem diameter, number of leaves, petiole length and length of roots of papaya seedlings. Analyses were performed from a blank trial with 240 seedlings of "Golden Pecíolo Curto". The determination of the optimum plot size was done by applying the methods of maximum curvature, maximum curvature of coefficient of variation and a new proposed method, which incorporates the bootstrap resampling simulation to the maximum curvature method. According to the results obtained, five is the optimal number of seedlings of papaya "Golden Pecíolo Curto" per plot. The proposed method of bootstrap simulation with replacement provides optimal plot sizes equal or higher than the maximum curvature method and provides same plot size than maximum curvature method of the coefficient of variation.

  20. The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem

    Science.gov (United States)

    Chen, Zhong; Liu, June; Li, Xiong

    2017-01-01

    A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced set. In order to illustrate the proposed method, seven numerical examples are tested and compared with results in the classical literature. Finally, a practical problem is solved by the proposed algorithm. PMID:29312446

  1. An Energy Efficiency Evaluation Method Based on Energy Baseline for Chemical Industry

    OpenAIRE

    Yao, Dong-mei; Zhang, Xin; Wang, Ke-feng; Zou, Tao; Wang, Dong; Qian, Xin-hua

    2016-01-01

    According to the requirements and structure of ISO 50001 energy management system, this study proposes an energy efficiency evaluation method based on energy baseline for chemical industry. Using this method, the energy plan implementation effect in the processes of chemical production can be evaluated quantitatively, and evidences for system fault diagnosis can be provided. This method establishes the energy baseline models which can meet the demand of the different kinds of production proce...

  2. Stress and deflection analyses of floating roofs based on a load-modifying method

    International Nuclear Information System (INIS)

    Sun Xiushan; Liu Yinghua; Wang Jianbin; Cen Zhangzhi

    2008-01-01

    This paper proposes a load-modifying method for the stress and deflection analyses of floating roofs used in cylindrical oil storage tanks. The formulations of loads and deformations are derived according to the equilibrium analysis of floating roofs. Based on these formulations, the load-modifying method is developed to conduct a geometrically nonlinear analysis of floating roofs with the finite element (FE) simulation. In the procedure with the load-modifying method, the analysis is carried out through a series of iterative computations until a convergence is achieved within the error tolerance. Numerical examples are given to demonstrate the validity and reliability of the proposed method, which provides an effective and practical numerical solution to the design and analysis of floating roofs

  3. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  4. Multi-band Image Registration Method Based on Fourier Transform

    Institute of Scientific and Technical Information of China (English)

    庹红娅; 刘允才

    2004-01-01

    This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.

  5. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  6. A combined emitter threat assessment method based on ICW-RCM

    Science.gov (United States)

    Zhang, Ying; Wang, Hongwei; Guo, Xiaotao; Wang, Yubing

    2017-08-01

    Considering that the tradition al emitter threat assessment methods are difficult to intuitively reflect the degree of target threaten and the deficiency of real-time and complexity, on the basis of radar chart method(RCM), an algorithm of emitter combined threat assessment based on ICW-RCM (improved combination weighting method, ICW) is proposed. The coarse sorting is integrated with fine sorting in emitter combined threat assessment, sequencing the emitter threat level roughly accordance to radar operation mode, and reducing task priority of the low-threat emitter; On the basis of ICW-RCM, sequencing the same radar operation mode emitter roughly, finally, obtain the results of emitter threat assessment through coarse and fine sorting. Simulation analyses show the correctness and effectiveness of this algorithm. Comparing with classical method of emitter threat assessment based on CW-RCM, the algorithm is visual in image and can work quickly with lower complexity.

  7. Reliability analysis based on a novel density estimation method for structures with correlations

    Directory of Open Access Journals (Sweden)

    Baoyu LI

    2017-06-01

    Full Text Available Estimating the Probability Density Function (PDF of the performance function is a direct way for structural reliability analysis, and the failure probability can be easily obtained by integration in the failure domain. However, efficiently estimating the PDF is still an urgent problem to be solved. The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation, whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs. While in fact, structures with correlated inputs always exist in engineering, thus this paper improves the maximum entropy method, and applies the Unscented Transformation (UT technique to compute the fractional moments of the performance function for structures with correlations, which is a very efficient moment estimation method for models with any inputs. The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations. Besides, the number of function evaluations of the proposed method in reliability analysis, which is determined by UT, is really small. Several examples are employed to illustrate the accuracy and advantages of the proposed method.

  8. Adaptive variational mode decomposition method for signal processing based on mode characteristic

    Science.gov (United States)

    Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

    2018-07-01

    Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

  9. A novel method for energy harvesting simulation based on scenario generation

    Science.gov (United States)

    Wang, Zhe; Li, Taoshen; Xiao, Nan; Ye, Jin; Wu, Min

    2018-06-01

    Energy harvesting network (EHN) is a new form of computer networks. It converts ambient energy into usable electric energy and supply the electrical energy as a primary or secondary power source to the communication devices. However, most of the EHN uses the analytical probability distribution function to describe the energy harvesting process, which cannot accurately identify the actual situation for the lack of authenticity. We propose an EHN simulation method based on scenario generation in this paper. Firstly, instead of setting a probability distribution in advance, it uses optimal scenario reduction technology to generate representative scenarios in single period based on the historical data of the harvested energy. Secondly, it uses homogeneous simulated annealing algorithm to generate optimal daily energy harvesting scenario sequences to get a more accurate simulation of the random characteristics of the energy harvesting network. Then taking the actual wind power data as an example, the accuracy and stability of the method are verified by comparing with the real data. Finally, we cite an instance to optimize the network throughput, which indicate the feasibility and effectiveness of the method we proposed from the optimal solution and data analysis in energy harvesting simulation.

  10. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  11. A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2015-12-01

    Full Text Available Estimating the residual capacity or state-of-charge (SoC of commercial batteries on-line without destroying them or interrupting the power supply, is quite a challenging task for electric vehicle (EV designers. Many Coulomb counting-based methods have been used to calculate the remaining capacity in EV batteries or other portable devices. The main disadvantages of these methods are the cumulative error and the time-varying Coulombic efficiency, which are greatly influenced by the operating state (SoC, temperature and current. To deal with this problem, we propose a lossy counting-based Coulomb counting method for estimating the available capacity or SoC. The initial capacity of the tested battery is obtained from the open circuit voltage (OCV. The charging/discharging efficiencies, used for compensating the Coulombic losses, are calculated by the lossy counting-based method. The measurement drift, resulting from the current sensor, is amended with the distorted Coulombic efficiency matrix. Simulations and experimental results show that the proposed method is both effective and convenient.

  12. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

    Directory of Open Access Journals (Sweden)

    Yun Tian

    2016-01-01

    Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

  13. A new physics-based method for detecting weak nuclear signals via spectral decomposition

    International Nuclear Information System (INIS)

    Chan, Kung-Sik; Li, Jinzheng; Eichinger, William; Bai, Erwei

    2012-01-01

    We propose a new physics-based method to determine the presence of the spectral signature of one or more nuclides from a poorly resolved spectra with weak signatures. The method is different from traditional methods that rely primarily on peak finding algorithms. The new approach considers each of the signatures in the library to be a linear combination of subspectra. These subspectra are obtained by assuming a signature consisting of just one of the unique gamma rays emitted by the nuclei. We propose a Poisson regression model for deducing which nuclei are present in the observed spectrum. In recognition that a radiation source generally comprises few nuclear materials, the underlying Poisson model is sparse, i.e. most of the regression coefficients are zero (positive coefficients correspond to the presence of nuclear materials). We develop an iterative algorithm for a penalized likelihood estimation that prompts sparsity. We illustrate the efficacy of the proposed method by simulations using a variety of poorly resolved, low signal-to-noise ratio (SNR) situations, which show that the proposed approach enjoys excellent empirical performance even with SNR as low as to -15 db.

  14. An efficient modularized sample-based method to estimate the first-order Sobol' index

    International Nuclear Information System (INIS)

    Li, Chenzhao; Mahadevan, Sankaran

    2016-01-01

    Sobol' index is a prominent methodology in global sensitivity analysis. This paper aims to directly estimate the Sobol' index based only on available input–output samples, even if the underlying model is unavailable. For this purpose, a new method to calculate the first-order Sobol' index is proposed. The innovation is that the conditional variance and mean in the formula of the first-order index are calculated at an unknown but existing location of model inputs, instead of an explicit user-defined location. The proposed method is modularized in two aspects: 1) index calculations for different model inputs are separate and use the same set of samples; and 2) model input sampling, model evaluation, and index calculation are separate. Due to this modularization, the proposed method is capable to compute the first-order index if only input–output samples are available but the underlying model is unavailable, and its computational cost is not proportional to the dimension of the model inputs. In addition, the proposed method can also estimate the first-order index with correlated model inputs. Considering that the first-order index is a desired metric to rank model inputs but current methods can only handle independent model inputs, the proposed method contributes to fill this gap. - Highlights: • An efficient method to estimate the first-order Sobol' index. • Estimate the index from input–output samples directly. • Computational cost is not proportional to the number of model inputs. • Handle both uncorrelated and correlated model inputs.

  15. A proposal for evaluation method of crack growth due to cyclic overload for piping materials based on an elastic-plastic fracture mechanics parameter

    International Nuclear Information System (INIS)

    Yamaguchi, Yoshihito; Katsuyama, Jinya; Onizawa, Kunio; Li, Yinsheng; Sugino, Hideharu

    2011-01-01

    The magnitude of Niigata-ken Chuetsu-Oki earthquake in 2007 was beyond the assumed one provided in seismic design. Therefore it becomes an important issue to evaluate the crack growth behaviors due to the cyclic overload like large earthquake. Fatigue crack growth is usually evaluated by Paris's law using the range of stress intensity factor (ΔK). However, ΔK is inappropriate in a loading condition beyond small scale yielding. In this study, the crack growth behaviors for piping materials were investigated based on an elastic-plastic fracture mechanics parameter, J-integral. It was indicated that the crack growth due to the cyclic overload beyond small scale yielding could be the sum of fatigue and ductile crack growth. The retardation effect of excessive loading on the crack growth was observed after the loading. The modified Wheeler model using J-integral has been proposed for the prediction of retardation effect. Finally, an evaluation method for crack growth behaviors due to the cyclic overload is suggested. (author)

  16. A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes

    Directory of Open Access Journals (Sweden)

    Detong Kong

    2012-02-01

    Full Text Available Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.

  17. A Trial-and-Error Method with Autonomous Vehicle-to-Infrastructure Traffic Counts for Cordon-Based Congestion Pricing

    Directory of Open Access Journals (Sweden)

    Zhiyuan Liu

    2017-01-01

    Full Text Available This study proposes a practical trial-and-error method to solve the optimal toll design problem of cordon-based pricing, where only the traffic counts autonomously collected on the entry links of the pricing cordon are needed. With the fast development and adoption of vehicle-to-infrastructure (V2I facilities, it is very convenient to autonomously collect these data. Two practical properties of the cordon-based pricing are further considered in this article: the toll charge on each entry of one pricing cordon is identical; the total inbound flow to one cordon should be restricted in order to maintain the traffic conditions within the cordon area. Then, the stochastic user equilibrium (SUE with asymmetric link travel time functions is used to assess each feasible toll pattern. Based on a variational inequality (VI model for the optimal toll pattern, this study proposes a theoretically convergent trial-and-error method for the addressed problem, where only traffic counts data are needed. Finally, the proposed method is verified based on a numerical network example.

  18. Network reliability analysis of complex systems using a non-simulation-based method

    International Nuclear Information System (INIS)

    Kim, Youngsuk; Kang, Won-Hee

    2013-01-01

    Civil infrastructures such as transportation, water supply, sewers, telecommunications, and electrical and gas networks often establish highly complex networks, due to their multiple source and distribution nodes, complex topology, and functional interdependence between network components. To understand the reliability of such complex network system under catastrophic events such as earthquakes and to provide proper emergency management actions under such situation, efficient and accurate reliability analysis methods are necessary. In this paper, a non-simulation-based network reliability analysis method is developed based on the Recursive Decomposition Algorithm (RDA) for risk assessment of generic networks whose operation is defined by the connections of multiple initial and terminal node pairs. The proposed method has two separate decomposition processes for two logical functions, intersection and union, and combinations of these processes are used for the decomposition of any general system event with multiple node pairs. The proposed method is illustrated through numerical network examples with a variety of system definitions, and is applied to a benchmark gas transmission pipe network in Memphis TN to estimate the seismic performance and functional degradation of the network under a set of earthquake scenarios.

  19. Hesitant fuzzy linguistic multicriteria decision-making method based on generalized prioritized aggregation operator.

    Science.gov (United States)

    Wu, Jia-ting; Wang, Jian-qiang; Wang, Jing; Zhang, Hong-yu; Chen, Xiao-hong

    2014-01-01

    Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

  20. Objective video quality assessment method for freeze distortion based on freeze aggregation

    Science.gov (United States)

    Watanabe, Keishiro; Okamoto, Jun; Kurita, Takaaki

    2006-01-01

    With the development of the broadband network, video communications such as videophone, video distribution, and IPTV services are beginning to become common. In order to provide these services appropriately, we must manage them based on subjective video quality, in addition to designing a network system based on it. Currently, subjective quality assessment is the main method used to quantify video quality. However, it is time-consuming and expensive. Therefore, we need an objective quality assessment technology that can estimate video quality from video characteristics effectively. Video degradation can be categorized into two types: spatial and temporal. Objective quality assessment methods for spatial degradation have been studied extensively, but methods for temporal degradation have hardly been examined even though it occurs frequently due to network degradation and has a large impact on subjective quality. In this paper, we propose an objective quality assessment method for temporal degradation. Our approach is to aggregate multiple freeze distortions into an equivalent freeze distortion and then derive the objective video quality from the equivalent freeze distortion. Specifically, our method considers the total length of all freeze distortions in a video sequence as the length of the equivalent single freeze distortion. In addition, we propose a method using the perceptual characteristics of short freeze distortions. We verified that our method can estimate the objective video quality well within the deviation of subjective video quality.

  1. A particle-based method for granular flow simulation

    KAUST Repository

    Chang, Yuanzhang; Bao, Kai; Zhu, Jian; Wu, Enhua

    2012-01-01

    We present a new particle-based method for granular flow simulation. In the method, a new elastic stress term, which is derived from a modified form of the Hooke's law, is included in the momentum governing equation to handle the friction of granular materials. Viscosity force is also added to simulate the dynamic friction for the purpose of smoothing the velocity field and further maintaining the simulation stability. Benefiting from the Lagrangian nature of the SPH method, large flow deformation can be well handled easily and naturally. In addition, a signed distance field is also employed to enforce the solid boundary condition. The experimental results show that the proposed method is effective and efficient for handling the flow of granular materials, and different kinds of granular behaviors can be well simulated by adjusting just one parameter. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.

  2. A particle-based method for granular flow simulation

    KAUST Repository

    Chang, Yuanzhang

    2012-03-16

    We present a new particle-based method for granular flow simulation. In the method, a new elastic stress term, which is derived from a modified form of the Hooke\\'s law, is included in the momentum governing equation to handle the friction of granular materials. Viscosity force is also added to simulate the dynamic friction for the purpose of smoothing the velocity field and further maintaining the simulation stability. Benefiting from the Lagrangian nature of the SPH method, large flow deformation can be well handled easily and naturally. In addition, a signed distance field is also employed to enforce the solid boundary condition. The experimental results show that the proposed method is effective and efficient for handling the flow of granular materials, and different kinds of granular behaviors can be well simulated by adjusting just one parameter. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.

  3. Risk assessment for pipelines with active defects based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Anghel, Calin I. [Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, University ' Babes-Bolyai' , Cluj-Napoca (Romania)], E-mail: canghel@chem.ubbcluj.ro

    2009-07-15

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  4. Risk assessment for pipelines with active defects based on artificial intelligence methods

    International Nuclear Information System (INIS)

    Anghel, Calin I.

    2009-01-01

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  5. A hybrid degradation tendency measurement method for mechanical equipment based on moving window and Grey–Markov model

    International Nuclear Information System (INIS)

    Jiang, Wei; Zhou, Jianzhong; Zheng, Yang; Liu, Han

    2017-01-01

    Accurate degradation tendency measurement is vital for the secure operation of mechanical equipment. However, the existing techniques and methodologies for degradation measurement still face challenges, such as lack of appropriate degradation indicator, insufficient accuracy, and poor capability to track the data fluctuation. To solve these problems, a hybrid degradation tendency measurement method for mechanical equipment based on a moving window and Grey–Markov model is proposed in this paper. In the proposed method, a 1D normalized degradation index based on multi-feature fusion is designed to assess the extent of degradation. Subsequently, the moving window algorithm is integrated with the Grey–Markov model for the dynamic update of the model. Two key parameters, namely the step size and the number of states, contribute to the adaptive modeling and multi-step prediction. Finally, three types of combination prediction models are established to measure the degradation trend of equipment. The effectiveness of the proposed method is validated with a case study on the health monitoring of turbine engines. Experimental results show that the proposed method has better performance, in terms of both measuring accuracy and data fluctuation tracing, in comparison with other conventional methods. (paper)

  6. A hybrid degradation tendency measurement method for mechanical equipment based on moving window and Grey-Markov model

    Science.gov (United States)

    Jiang, Wei; Zhou, Jianzhong; Zheng, Yang; Liu, Han

    2017-11-01

    Accurate degradation tendency measurement is vital for the secure operation of mechanical equipment. However, the existing techniques and methodologies for degradation measurement still face challenges, such as lack of appropriate degradation indicator, insufficient accuracy, and poor capability to track the data fluctuation. To solve these problems, a hybrid degradation tendency measurement method for mechanical equipment based on a moving window and Grey-Markov model is proposed in this paper. In the proposed method, a 1D normalized degradation index based on multi-feature fusion is designed to assess the extent of degradation. Subsequently, the moving window algorithm is integrated with the Grey-Markov model for the dynamic update of the model. Two key parameters, namely the step size and the number of states, contribute to the adaptive modeling and multi-step prediction. Finally, three types of combination prediction models are established to measure the degradation trend of equipment. The effectiveness of the proposed method is validated with a case study on the health monitoring of turbine engines. Experimental results show that the proposed method has better performance, in terms of both measuring accuracy and data fluctuation tracing, in comparison with other conventional methods.

  7. Testing the ability of a proposed geotechnical based method to evaluate the liquefaction potential analysis subjected to earthquake vibrations

    Science.gov (United States)

    Abbaszadeh Shahri, A.; Behzadafshar, K.; Esfandiyari, B.; Rajablou, R.

    2010-12-01

    During the earthquakes a number of earth dams have had severe damages or suffered major displacements as a result of liquefaction, thus modeling by computer codes can provide a reliable tool to predict the response of the dam foundation against earthquakes. These modeling can be used in the design of new dams or safety assessments of existing ones. In this paper, on base of the field and laboratory tests and by combination of several software packages a seismic geotechnical based analysis procedure is proposed and verified by comparison with computer model tests, field and laboratory experiences. Verification or validation of the analyses relies to ability of the applied computer codes. By use of Silakhor earthquake (2006, Ms 6.1) and in order to check the efficiency of the proposed framework, the procedure is applied to the Korzan earth dam of Iran which is located in Hamedan Province to analyze and estimate the liquefaction and safety factor. Design and development of a computer code by authors which named as “Abbas Converter” with graphical user interface which operates as logic connecter function that can computes and models the soil profiles is the critical point of this study and the results are confirm and proved the ability of the generated computer code on evaluation of soil behavior under the earthquake excitations. Also this code can make and render facilitate this study more than previous have done, and take over the encountered problem.

  8. New Internet search volume-based weighting method for integrating various environmental impacts

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Changyoon, E-mail: changyoon@yonsei.ac.kr; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr

    2016-01-15

    Weighting is one of the steps in life cycle impact assessment that integrates various characterized environmental impacts as a single index. Weighting factors should be based on the society's preferences. However, most previous studies consider only the opinion of some people. Thus, this research proposes a new weighting method that determines the weighting factors of environmental impact categories by considering public opinion on environmental impacts using the Internet search volumes for relevant terms. To validate the new weighting method, the weighting factors for six environmental impacts calculated by the new weighting method were compared with the existing weighting factors. The resulting Pearson's correlation coefficient between the new and existing weighting factors was from 0.8743 to 0.9889. It turned out that the new weighting method presents reasonable weighting factors. It also requires less time and lower cost compared to existing methods and likewise meets the main requirements of weighting methods such as simplicity, transparency, and reproducibility. The new weighting method is expected to be a good alternative for determining the weighting factor. - Highlight: • A new weighting method using Internet search volume is proposed in this research. • The new weighting method reflects the public opinion using Internet search volume. • The correlation coefficient between new and existing weighting factors is over 0.87. • The new weighting method can present the reasonable weighting factors. • The proposed method can be a good alternative for determining the weighting factors.

  9. New Internet search volume-based weighting method for integrating various environmental impacts

    International Nuclear Information System (INIS)

    Ji, Changyoon; Hong, Taehoon

    2016-01-01

    Weighting is one of the steps in life cycle impact assessment that integrates various characterized environmental impacts as a single index. Weighting factors should be based on the society's preferences. However, most previous studies consider only the opinion of some people. Thus, this research proposes a new weighting method that determines the weighting factors of environmental impact categories by considering public opinion on environmental impacts using the Internet search volumes for relevant terms. To validate the new weighting method, the weighting factors for six environmental impacts calculated by the new weighting method were compared with the existing weighting factors. The resulting Pearson's correlation coefficient between the new and existing weighting factors was from 0.8743 to 0.9889. It turned out that the new weighting method presents reasonable weighting factors. It also requires less time and lower cost compared to existing methods and likewise meets the main requirements of weighting methods such as simplicity, transparency, and reproducibility. The new weighting method is expected to be a good alternative for determining the weighting factor. - Highlight: • A new weighting method using Internet search volume is proposed in this research. • The new weighting method reflects the public opinion using Internet search volume. • The correlation coefficient between new and existing weighting factors is over 0.87. • The new weighting method can present the reasonable weighting factors. • The proposed method can be a good alternative for determining the weighting factors.

  10. Proposed method for assigning metric tons of heavy metal values to defense high-level waste forms to be disposed of in a geologic repository

    International Nuclear Information System (INIS)

    1987-08-01

    A proposed method is described for assigning an equivalent metric ton heavy metal (eMTHM) value to defense high-level waste forms to be disposed of in a geologic repository. This method for establishing a curie equivalency between defense high-level waste and irradiated commercial fuel is based on the ratio of defense fuel exposure to the typical commercial fuel exposure, MWd/MTHM. application of this technique to defense high-level wastes is described. Additionally, this proposed technique is compared to several alternate calculations for eMTHM. 15 refs., 2 figs., 10 tabs

  11. A fault diagnosis method based on signed directed graph and matrix for nuclear power plants

    International Nuclear Information System (INIS)

    Liu, Yong-Kuo; Wu, Guo-Hua; Xie, Chun-Li; Duan, Zhi-Yong; Peng, Min-Jun; Li, Meng-Kun

    2016-01-01

    Highlights: • “Rules matrix” is proposed for FDD. • “State matrix” is proposed to solve SDG online inference. • SDG inference and search method are combined for FDD. - Abstract: In order to solve SDG online fault diagnosis and inference, matrix diagnosis and inference methods are proposed for fault detection and diagnosis (FDD). Firstly, “rules matrix” based on SDG model is used for FDD. Secondly, “status matrix” is proposed to achieve SDG online inference. According to different diagnosis results, “status matrix” is applied for the depth-first search and the breadth-first search respectively to find the propagation paths of each fault. Finally, the SDG model of the secondary-loop system in pressurized water reactor (PWR) is built to verify the effectiveness of the proposed method. The simulation experiment results indicate that the “status matrix” used for online inference can be used to find the fault propagation paths and to explain the causes for fault. Therefore, it can be concluded that the proposed method is one of the fault diagnosis for nuclear power plants (NPPs), which can be used to facilitate the development of fault diagnostic system.

  12. A fault diagnosis method based on signed directed graph and matrix for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yong-Kuo, E-mail: LYK08@126.com [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China); Wu, Guo-Hua [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China); Institute of Nuclear Energy Technology, Tsinghua University, Beijing 100084 (China); Xie, Chun-Li [Traffic College, Northeast Forestry University, Harbin, 150040 (China); Duan, Zhi-Yong; Peng, Min-Jun; Li, Meng-Kun [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China)

    2016-02-15

    Highlights: • “Rules matrix” is proposed for FDD. • “State matrix” is proposed to solve SDG online inference. • SDG inference and search method are combined for FDD. - Abstract: In order to solve SDG online fault diagnosis and inference, matrix diagnosis and inference methods are proposed for fault detection and diagnosis (FDD). Firstly, “rules matrix” based on SDG model is used for FDD. Secondly, “status matrix” is proposed to achieve SDG online inference. According to different diagnosis results, “status matrix” is applied for the depth-first search and the breadth-first search respectively to find the propagation paths of each fault. Finally, the SDG model of the secondary-loop system in pressurized water reactor (PWR) is built to verify the effectiveness of the proposed method. The simulation experiment results indicate that the “status matrix” used for online inference can be used to find the fault propagation paths and to explain the causes for fault. Therefore, it can be concluded that the proposed method is one of the fault diagnosis for nuclear power plants (NPPs), which can be used to facilitate the development of fault diagnostic system.

  13. High viscosity fluid simulation using particle-based method

    KAUST Repository

    Chang, Yuanzhang

    2011-03-01

    We present a new particle-based method for high viscosity fluid simulation. In the method, a new elastic stress term, which is derived from a modified form of the Hooke\\'s law, is included in the traditional Navier-Stokes equation to simulate the movements of the high viscosity fluids. Benefiting from the Lagrangian nature of Smoothed Particle Hydrodynamics method, large flow deformation can be well handled easily and naturally. In addition, in order to eliminate the particle deficiency problem near the boundary, ghost particles are employed to enforce the solid boundary condition. Compared with Finite Element Methods with complicated and time-consuming remeshing operations, our method is much more straightforward to implement. Moreover, our method doesn\\'t need to store and compare to an initial rest state. The experimental results show that the proposed method is effective and efficient to handle the movements of highly viscous flows, and a large variety of different kinds of fluid behaviors can be well simulated by adjusting just one parameter. © 2011 IEEE.

  14. Improvement of Power Flow Calculation with Optimization Factor Based on Current Injection Method

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2014-01-01

    Full Text Available This paper presents an improvement in power flow calculation based on current injection method by introducing optimization factor. In the method proposed by this paper, the PQ buses are represented by current mismatches while the PV buses are represented by power mismatches. It is different from the representations in conventional current injection power flow equations. By using the combined power and current injection mismatches method, the number of the equations required can be decreased to only one for each PV bus. The optimization factor is used to improve the iteration process and to ensure the effectiveness of the improved method proposed when the system is ill-conditioned. To verify the effectiveness of the method, the IEEE test systems are tested by conventional current injection method and the improved method proposed separately. Then the results are compared. The comparisons show that the optimization factor improves the convergence character effectively, especially that when the system is at high loading level and R/X ratio, the iteration number is one or two times less than the conventional current injection method. When the overloading condition of the system is serious, the iteration number in this paper appears 4 times less than the conventional current injection method.

  15. A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2016-02-01

    Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

  16. Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

    International Nuclear Information System (INIS)

    Chen, Xudong

    2010-01-01

    This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging

  17. The Proposal to “Snapshot” Raim Method for Gnss Vessel Receivers Working in Poor Space Segment Geometry

    Directory of Open Access Journals (Sweden)

    Nowak Aleksander

    2015-12-01

    Full Text Available Nowadays, we can observe an increase in research on the use of small unmanned autonomous vessel (SUAV to patrol and guiding critical areas including harbours. The proposal to “snapshot” RAIM (Receiver Autonomous Integrity Monitoring method for GNSS receivers mounted on SUAV operating in poor space segment geometry is presented in the paper. Existing “snapshot” RAIM methods and algorithms which are used in practical applications have been developed for airborne receivers, thus two main assumptions have been made. The first one is that the geometry of visible satellites is strong. It means that the exclusion of any satellite from the positioning solution don’t cause significant deterioration of Dilution of Precision (DOP coefficients. The second one is that only one outlier could appear in pseudorange measurements. In case of SUAV operating in harbour these two assumptions cannot be accepted. Because of their small dimensions, GNSS antenna is only a few decimetres above sea level and regular ships, buildings and harbour facilities block and reflect satellite signals. Thus, different approach to “snapshot” RAIM is necessary. The proposal to method based on analyses of allowable maximal separation of positioning sub-solutions with using some information from EGNOS messages is described in the paper. Theoretical assumptions and results of numerical experiments are presented.

  18. A proposal for an SDN-based SIEPON architecture

    Science.gov (United States)

    Khalili, Hamzeh; Sallent, Sebastià; Piney, José Ramón; Rincón, David

    2017-11-01

    Passive Optical Network (PON) elements such as Optical Line Terminal (OLT) and Optical Network Units (ONUs) are currently managed by inflexible legacy network management systems. Software-Defined Networking (SDN) is a new networking paradigm that improves the operation and management of networks. In this paper, we propose a novel architecture, based on the SDN concept, for Ethernet Passive Optical Networks (EPON) that includes the Service Interoperability standard (SIEPON). In our proposal, the OLT is partially virtualized and some of its functionalities are allocated to the core network management system, while the OLT itself is replaced by an OpenFlow (OF) switch. A new MultiPoint MAC Control (MPMC) sublayer extension based on the OpenFlow protocol is presented. This would allow the SDN controller to manage and enhance the resource utilization, flow monitoring, bandwidth assignment, quality-of-service (QoS) guarantees, and energy management of the optical network access, to name a few possibilities. The OpenFlow switch is extended with synchronous ports to retain the time-critical nature of the EPON network. OpenFlow messages are also extended with new functionalities to implement the concept of EPON Service Paths (ESPs). Our simulation-based results demonstrate the effectiveness of the new architecture, while retaining a similar (or improved) performance in terms of delay and throughput when compared to legacy PONs.

  19. A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing

    Directory of Open Access Journals (Sweden)

    Huimin Zhao

    2016-12-01

    Full Text Available Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD, mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery.

  20. Chaos M-ary modulation and demodulation method based on Hamilton oscillator and its application in communication.

    Science.gov (United States)

    Fu, Yongqing; Li, Xingyuan; Li, Yanan; Yang, Wei; Song, Hailiang

    2013-03-01

    Chaotic communication has aroused general interests in recent years, but its communication effect is not ideal with the restriction of chaos synchronization. In this paper a new chaos M-ary digital modulation and demodulation method is proposed. By using region controllable characteristics of spatiotemporal chaos Hamilton map in phase plane and chaos unique characteristic, which is sensitive to initial value, zone mapping method is proposed. It establishes the map relationship between M-ary digital information and the region of Hamilton map phase plane, thus the M-ary information chaos modulation is realized. In addition, zone partition demodulation method is proposed based on the structure characteristic of Hamilton modulated information, which separates M-ary information from phase trajectory of chaotic Hamilton map, and the theory analysis of zone partition demodulator's boundary range is given. Finally, the communication system based on the two methods is constructed on the personal computer. The simulation shows that in high speed transmission communications and with no chaos synchronization circumstance, the proposed chaotic M-ary modulation and demodulation method has outperformed some conventional M-ary modulation methods, such as quadrature phase shift keying and M-ary pulse amplitude modulation in bit error rate. Besides, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-noise performance, and the system complexity is low and chaos signal is easy to generate.

  1. An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

    Science.gov (United States)

    Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

    2018-04-01

    Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

  2. A shape-based quality evaluation and reconstruction method for electrical impedance tomography.

    Science.gov (United States)

    Antink, Christoph Hoog; Pikkemaat, Robert; Malmivuo, Jaakko; Leonhardt, Steffen

    2015-06-01

    Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community. In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed. Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images.

  3. An accuracy measurement method for star trackers based on direct astronomic observation.

    Science.gov (United States)

    Sun, Ting; Xing, Fei; Wang, Xiaochu; You, Zheng; Chu, Daping

    2016-03-07

    Star tracker is one of the most promising optical attitude measurement devices and it is widely used in spacecraft for its high accuracy. However, how to realize and verify such an accuracy remains a crucial but unsolved issue until now. The authenticity of the accuracy measurement method of a star tracker will eventually determine the satellite performance. A new and robust accuracy measurement method for a star tracker based on the direct astronomical observation is proposed here. In comparison with the conventional method with simulated stars, this method utilizes real navigation stars as observation targets which makes the measurement results more authoritative and authentic. Transformations between different coordinate systems are conducted on the account of the precision movements of the Earth, and the error curves of directional vectors are obtained along the three axes. Based on error analysis and accuracy definitions, a three-axis accuracy evaluation criterion has been proposed in this paper, which could determine pointing and rolling accuracy of a star tracker directly. Experimental measurements confirm that this method is effective and convenient to implement. Such a measurement environment is close to the in-orbit conditions and it can satisfy the stringent requirement for high-accuracy star trackers.

  4. A shape-based quality evaluation and reconstruction method for electrical impedance tomography

    International Nuclear Information System (INIS)

    Antink, Christoph Hoog; Pikkemaat, Robert; Leonhardt, Steffen; Malmivuo, Jaakko

    2015-01-01

    Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community.In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed.Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images. (paper)

  5. A method of distributed avionics data processing based on SVM classifier

    Science.gov (United States)

    Guo, Hangyu; Wang, Jinyan; Kang, Minyang; Xu, Guojing

    2018-03-01

    Under the environment of system combat, in order to solve the problem on management and analysis of the massive heterogeneous data on multi-platform avionics system, this paper proposes a management solution which called avionics "resource cloud" based on big data technology, and designs an aided decision classifier based on SVM algorithm. We design an experiment with STK simulation, the result shows that this method has a high accuracy and a broad application prospect.

  6. Visual improvement for bad handwriting based on Monte-Carlo method

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

    2014-03-01

    A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

  7. EOP Improvement Proposal for SGTR based on The OPR PSA Update

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jin Hee; Cho, Jae Hyun; Kim, Dong San; Yang, Joon Eon [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    This updating process was also focused to enhance the PSA quality and to respect the as built and as operated conditions of target plants. For this purpose, the EOP(Emergency Operating Procedure) and AOP(Abnormal Operating Procedure) of target plant were reviewed in detail and various thermal hydraulic(T/H) analysis were also performed to analyze the realistic PSA accident sequence model. In this paper, the unreasonable point of SGTR (Steam Generator Tube Rupture) EOP based on PSA perspective was identified and the initial proposal for EOP change items from PSA insight was proposed. In this paper, the unreasonable point of SGTR EOP based on PSA perspective was identified and the EOP improvement items are proposed to enhance safety and operator's convenience for the target plant.

  8. Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization

    OpenAIRE

    Deming Yuan

    2014-01-01

    This paper considers the constrained multiagent optimization problem. The objective function of the problem is a sum of convex functions, each of which is known by a specific agent only. For solving this problem, we propose an asynchronous distributed method that is based on gradient-free oracles and gossip algorithm. In contrast to the existing work, we do not require that agents be capable of computing the subgradients of their objective functions and coordinating their...

  9. Cross-Correlation-Function-Based Multipath Mitigation Method for Sine-BOC Signals

    Directory of Open Access Journals (Sweden)

    H. H. Chen

    2012-06-01

    Full Text Available Global Navigation Satellite Systems (GNSS positioning accuracy indoor and urban canyons environments are greatly affected by multipath due to distortions in its autocorrelation function. In this paper, a cross-correlation function between the received sine phased Binary Offset Carrier (sine-BOC modulation signal and the local signal is studied firstly, and a new multipath mitigation method based on cross-correlation function for sine-BOC signal is proposed. This method is implemented to create a cross-correlation function by designing the modulated symbols of the local signal. The theoretical analysis and simulation results indicate that the proposed method exhibits better multipath mitigation performance compared with the traditional Double Delta Correlator (DDC techniques, especially the medium/long delay multipath signals, and it is also convenient and flexible to implement by using only one correlator, which is the case of low-cost mass-market receivers.

  10. A method for determining customer requirement weights based on TFMF and TLR

    Science.gov (United States)

    Ai, Qingsong; Shu, Ting; Liu, Quan; Zhou, Zude; Xiao, Zheng

    2013-11-01

    'Customer requirements' (CRs) management plays an important role in enterprise systems (ESs) by processing customer-focused information. Quality function deployment (QFD) is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function (TFMF) and 2-tuple linguistic representation (TLR). To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.

  11. A human-machine cooperation route planning method based on improved A* algorithm

    Science.gov (United States)

    Zhang, Zhengsheng; Cai, Chao

    2011-12-01

    To avoid the limitation of common route planning method to blindly pursue higher Machine Intelligence and autoimmunization, this paper presents a human-machine cooperation route planning method. The proposed method includes a new A* path searing strategy based on dynamic heuristic searching and a human cooperated decision strategy to prune searching area. It can overcome the shortage of A* algorithm to fall into a local long term searching. Experiments showed that this method can quickly plan a feasible route to meet the macro-policy thinking.

  12. Power-Efficient Beacon Recognition Method Based on Periodic Wake-Up for Industrial Wireless Devices.

    Science.gov (United States)

    Song, Soonyong; Lee, Donghun; Jang, Ingook; Choi, Jinchul; Son, Youngsung

    2018-04-17

    Energy harvester-integrated wireless devices are attractive for generating semi-permanent power from wasted energy in industrial environments. The energy-harvesting wireless devices may have difficulty in their communication with access points due to insufficient power supply for beacon recognition during network initialization. In this manuscript, we propose a novel method of beacon recognition based on wake-up control to reduce instantaneous power consumption in the initialization procedure. The proposed method applies a moving window for the periodic wake-up of the wireless devices. For unsynchronized wireless devices, beacons are always located in the same positions within each beacon interval even though the starting offsets are unknown. Using these characteristics, the moving window checks the existence of the beacon associated withspecified resources in a beacon interval, checks again for neighboring resources at the next beacon interval, and so on. This method can reduce instantaneous power and generates a surplus of charging time. Thus, the proposed method alleviates the problems of power insufficiency in the network initialization. The feasibility of the proposed method is evaluated using computer simulations of power shortage in various energy-harvesting conditions.

  13. Comparison of Standard Culture-Based Method to Culture-Independent Method for Evaluation of Hygiene Effects on the Hand Microbiome

    Science.gov (United States)

    Leff, J.; Henley, J.; Tittl, J.; De Nardo, E.; Butler, M.; Griggs, R.; Fierer, N.

    2017-01-01

    ABSTRACT Hands play a critical role in the transmission of microbiota on one’s own body, between individuals, and on environmental surfaces. Effectively measuring the composition of the hand microbiome is important to hand hygiene science, which has implications for human health. Hand hygiene products are evaluated using standard culture-based methods, but standard test methods for culture-independent microbiome characterization are lacking. We sampled the hands of 50 participants using swab-based and glove-based methods prior to and following four hand hygiene treatments (using a nonantimicrobial hand wash, alcohol-based hand sanitizer [ABHS], a 70% ethanol solution, or tap water). We compared results among culture plate counts, 16S rRNA gene sequencing of DNA extracted directly from hands, and sequencing of DNA extracted from culture plates. Glove-based sampling yielded higher numbers of unique operational taxonomic units (OTUs) but had less diversity in bacterial community composition than swab-based sampling. We detected treatment-induced changes in diversity only by using swab-based samples (P hand hygiene industry methods and for future hand microbiome studies. On the basis of our results and previously published studies, we propose recommendations for best practices in hand microbiome research. PMID:28351915

  14. Work in process level definition: a method based on computer simulation and electre tri

    Directory of Open Access Journals (Sweden)

    Isaac Pergher

    2014-09-01

    Full Text Available This paper proposes a method for defining the levels of work in progress (WIP in productive environments managed by constant work in process (CONWIP policies. The proposed method combines the approaches of Computer Simulation and Electre TRI to support estimation of the adequate level of WIP and is presented in eighteen steps. The paper also presents an application example, performed on a metalworking company. The research method is based on Computer Simulation, supported by quantitative data analysis. The main contribution of the paper is its provision of a structured way to define inventories according to demand. With this method, the authors hope to contribute to the establishment of better capacity plans in production environments.

  15. Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2014-01-01

    Full Text Available Due to the passenger’s security, the recognized hidden faults in car engines are the most important work for a maintenance engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel fault recognition method based on the genetic algorithm (GA and the extension theory and also apply this method to the fault recognition of a practical car engine. The proposed recognition method has been tested on the Nissan Cefiro 2.0 engine and has also been compared to other traditional classification methods. Experimental results are of great effect regarding the hidden fault recognition of car engines, and the proposed method can also be applied to other industrial apparatus.

  16. A dental implant-based registration method for measuring mandibular kinematics using cone beam computed tomography-based fluoroscopy.

    Science.gov (United States)

    Lin, Cheng-Chung; Chen, Chien-Chih; Chen, Yunn-Jy; Lu, Tung-Wu; Hong, Shih-Wun

    2014-01-01

    This study aimed to develop and evaluate experimentally an implant-based registration method for measuring three-dimensional (3D) kinematics of the mandible and dental implants in the mandible based on dental cone beam computed tomography (CBCT), modified to include fluoroscopic function. The proposed implant-based registration method was based on the registration of CBCT data of implants/bones with single-plane fluoroscopy images. Seven registration conditions that included one to three implants were evaluated experimentally for their performance in a cadaveric porcine headmodel. The implant-based registration method was shown to have measurement errors (SD) of less than -0.2 (0.3) mm, 1.1 (2.2) mm, and 0.7 degrees (1.3 degrees) for the in-plane translation, out-of-plane translation, and all angular components, respectively, regardless of the number of implants used. The corresponding errors were reduced to less than -0.1 (0.1) mm, -0.3 (1.7) mm, and 0.5 degree (0.4 degree) when three implants were used. An implant-based registration method was developed to measure the 3D kinematics of the mandible/implants. With its high accuracy and reliability, the new method will be useful for measuring the 3D motion of the bones/implants for relevant applications.

  17. A new service-oriented grid-based method for AIoT application and implementation

    Science.gov (United States)

    Zou, Yiqin; Quan, Li

    2017-07-01

    The traditional three-layer Internet of things (IoT) model, which includes physical perception layer, information transferring layer and service application layer, cannot express complexity and diversity in agricultural engineering area completely. It is hard to categorize, organize and manage the agricultural things with these three layers. Based on the above requirements, we propose a new service-oriented grid-based method to set up and build the agricultural IoT. Considering the heterogeneous, limitation, transparency and leveling attributes of agricultural things, we propose an abstract model for all agricultural resources. This model is service-oriented and expressed with Open Grid Services Architecture (OGSA). Information and data of agricultural things were described and encapsulated by using XML in this model. Every agricultural engineering application will provide service by enabling one application node in this service-oriented grid. Description of Web Service Resource Framework (WSRF)-based Agricultural Internet of Things (AIoT) and the encapsulation method were also discussed in this paper for resource management in this model.

  18. A Robust Service Selection Method Based on Uncertain QoS

    Directory of Open Access Journals (Sweden)

    Yanping Chen

    2016-01-01

    Full Text Available Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.

  19. Quantum image pseudocolor coding based on the density-stratified method

    Science.gov (United States)

    Jiang, Nan; Wu, Wenya; Wang, Luo; Zhao, Na

    2015-05-01

    Pseudocolor processing is a branch of image enhancement. It dyes grayscale images to color images to make the images more beautiful or to highlight some parts on the images. This paper proposes a quantum image pseudocolor coding scheme based on the density-stratified method which defines a colormap and changes the density value from gray to color parallel according to the colormap. Firstly, two data structures: quantum image GQIR and quantum colormap QCR are reviewed or proposed. Then, the quantum density-stratified algorithm is presented. Based on them, the quantum realization in the form of circuits is given. The main advantages of the quantum version for pseudocolor processing over the classical approach are that it needs less memory and can speed up the computation. Two kinds of examples help us to describe the scheme further. Finally, the future work are analyzed.

  20. Impact of Costing and Cost Analysis Methods on the Result of the Period: Methods Based on Partial Cost Theory

    Directory of Open Access Journals (Sweden)

    Toma Maria

    2017-01-01

    Looking from this perspective, in the present paper we have proposed that objectives, to approach the full cost calculation methods based on partial costs (direct-costing on the product or direct-costing evolved, and comparing them to determine the effect they have on the outcome of the period.

  1. A phase quantification method based on EBSD data for a continuously cooled microalloyed steel

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, H.; Wynne, B.P.; Palmiere, E.J., E-mail: e.j.palmiere@sheffield.ac.uk

    2017-01-15

    Mechanical properties of steels depend on the phase constitutions of the final microstructures which can be related to the processing parameters. Therefore, accurate quantification of different phases is necessary to investigate the relationships between processing parameters, final microstructures and mechanical properties. Point counting on micrographs observed by optical or scanning electron microscopy is widely used as a phase quantification method, and different phases are discriminated according to their morphological characteristics. However, it is difficult to differentiate some of the phase constituents with similar morphology. Differently, for EBSD based phase quantification methods, besides morphological characteristics, other parameters derived from the orientation information can also be used for discrimination. In this research, a phase quantification method based on EBSD data in the unit of grains was proposed to identify and quantify the complex phase constitutions of a microalloyed steel subjected to accelerated coolings. Characteristics of polygonal ferrite/quasi-polygonal ferrite, acicular ferrite and bainitic ferrite on grain averaged misorientation angles, aspect ratios, high angle grain boundary fractions and grain sizes were analysed and used to develop the identification criteria for each phase. Comparing the results obtained by this EBSD based method and point counting, it was found that this EBSD based method can provide accurate and reliable phase quantification results for microstructures with relatively slow cooling rates. - Highlights: •A phase quantification method based on EBSD data in the unit of grains was proposed. •The critical grain area above which GAM angles are valid parameters was obtained. •Grain size and grain boundary misorientation were used to identify acicular ferrite. •High cooling rates deteriorate the accuracy of this EBSD based method.

  2. A Sparsity-Promoted Method Based on Majorization-Minimization for Weak Fault Feature Enhancement.

    Science.gov (United States)

    Ren, Bangyue; Hao, Yansong; Wang, Huaqing; Song, Liuyang; Tang, Gang; Yuan, Hongfang

    2018-03-28

    Fault transient impulses induced by faulty components in rotating machinery usually contain substantial interference. Fault features are comparatively weak in the initial fault stage, which renders fault diagnosis more difficult. In this case, a sparse representation method based on the Majorzation-Minimization (MM) algorithm is proposed to enhance weak fault features and extract the features from strong background noise. However, the traditional MM algorithm suffers from two issues, which are the choice of sparse basis and complicated calculations. To address these challenges, a modified MM algorithm is proposed in which a sparse optimization objective function is designed firstly. Inspired by the Basis Pursuit (BP) model, the optimization function integrates an impulsive feature-preserving factor and a penalty function factor. Second, a modified Majorization iterative method is applied to address the convex optimization problem of the designed function. A series of sparse coefficients can be achieved through iterating, which only contain transient components. It is noteworthy that there is no need to select the sparse basis in the proposed iterative method because it is fixed as a unit matrix. Then the reconstruction step is omitted, which can significantly increase detection efficiency. Eventually, envelope analysis of the sparse coefficients is performed to extract weak fault features. Simulated and experimental signals including bearings and gearboxes are employed to validate the effectiveness of the proposed method. In addition, comparisons are made to prove that the proposed method outperforms the traditional MM algorithm in terms of detection results and efficiency.

  3. Process-based project proposal risk management

    Directory of Open Access Journals (Sweden)

    Alok Kumar

    2016-12-01

    Full Text Available We all are aware of the organizational omnipresence. Projects within the organizations are ubiquitous too. Projects achieve their goals successfully if they are planned, scheduled, controlled and implemented well. The project lifecycle of initiating, planning, scheduling, controlling and implementing are very well-planned by project managers and the organizations. Successful projects have well-developed risk management plans to deal with situations impacting projects. Like any other organisation, a university does try to access funds for different purposes too. For such organisations, running a project is not the issue, rather getting a project proposal approved to fund a project is the key. Project proposal processing is done by the nodal office in every organisation. Usually, these nodal offices help in administration and submission of a project proposal for accessing funds. Seldom are these nodal project offices within the organizations facilitate a project proposal approval by proactively reaching out to the project managers. And as project managers prepare project proposals, little or no attention is made to prepare a project proposal risk plan so as to maximise project acquisition. Risk plans are submitted while preparing proposals but these risk plans cater to a requirement to address actual projects upon approval. Hence, a risk management plan for project proposal is either missing or very little effort is made to treat the risks inherent in project acquisition. This paper is an integral attempt to highlight the importance of risk treatment for project proposal stage as an extremely important step to preparing the risk management plan made for projects corresponding to their lifecycle phases. Several tools and techniques have been proposed in the paper to help and guide either the project owner (proposer or the main organisational unit responsible for project management. Development of tools and techniques to further enhance project

  4. Non-Contact Plant Growth Measurement Method and System Based on Ubiquitous Sensor Network Technologies

    Directory of Open Access Journals (Sweden)

    Intae Ryoo

    2011-04-01

    Full Text Available This paper proposes a non-contact plant growth measurement system using infrared sensors based on the ubiquitous sensor network (USN technology. The proposed system measures plant growth parameters such as the stem radius of plants using real-time non-contact methods, and generates diameter, cross-sectional area and thickening form of plant stems using this measured data. Non-contact sensors have been used not to cause any damage to plants during measurement of the growth parameters. Once the growth parameters are measured, they are transmitted to a remote server using the sensor network technology and analyzed in the application program server. The analyzed data are then provided for administrators and a group of interested users. The proposed plant growth measurement system has been designed and implemented using fixed-type and rotary-type infrared sensor based measurement methods and devices. Finally, the system performance is compared and verified with the measurement data that have been obtained by practical field experiments.