Spatial Frequency Scheduling for Uplink SC-FDMA based Linearly Precoded LTE Multiuser MIMO Systems
DEFF Research Database (Denmark)
Lin, Zihuai; Xiao, Pei; Sørensen, Troels Bundgaard
2010-01-01
This paper investigates the performance of the 3GPP Long Term Evolution (LTE) uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) based linearly precoded multiuserMultiple InputMultiple Output (MIMO) systems with frequency domain packet scheduling. A mathematical expression...
Comparative analysis of equalization methods for SC-FDMA
DEFF Research Database (Denmark)
Dogadaev, Anton Konstantinovich; Kozlov, Alexander; Ukhanova, Ann
2010-01-01
In this paper we introduce comparative analysis for different types of equalization schemes, based on the minimum mean square error (MMSE) optimization. The following types of equalizers were compared: linear equalization, decision feedback equalization (DFE) and turbo equalization. Performance...... and complexity of these schemes were tested for Single Carrier Frequency Division Multiple Access (SC-FDMA) system with Single Input Single Output (SISO) antenna configuration. SC-FDMA is a common technique, which is used in the UTRA LTE Uplink, so the results of complexity and performance analysis could...... be applied to find the appropriate equalization algorithm to be used in the Uplink channel of the LTE – the famous standard in 4G telecommunications. Simulation results in the end in this paper show bit error ratio (BER) and modulation error ratio (MER) for compared schemes....
Performance Analysis of a Modified SC-FDMA-DSCDMA Technique for 4G Wireless Communication
Directory of Open Access Journals (Sweden)
Deepak Kedia
2014-01-01
Full Text Available Single-carrier FDMA (SC-FDMA is becoming more and more popular in multiuser communication because of its lower PAPR value. Apart from this, many other hybrid access techniques have also been explored in the literature for application to 4G wireless mobile communication. Still there is a need to explore newer techniques which could further reduce the PAPR value without any degradation in system BER. Keeping this in view, a modified hybrid technique SC-FDMA-DSCDMA has been proposed in this paper and it is found to provide significantly lower PAPR than SC-FDMA system with no degradation in BER performance. This paper extensively compares the BER and PAPR performance of various other multicarrier techniques for 4G wireless communications such as OFDMA, MC-DS-CDMA, and SC-FDMA with proposed SC-FDMA-DSCDMA scheme. Simulation results show that SC-FDMA-DSCDMA technique performs better than any other OFDM-CDMA based system for wireless communication.
Bayesian narrowband interference mitigation in SC-FDMA
Ali, Anum
2015-08-12
This paper presents a novel narrowband interference (NBI) mitigation scheme for SC-FDMA systems. The proposed scheme exploits the frequency domain sparsity of the unknown NBI signal and adopts a low complexity Bayesian sparse recovery procedure. In practice, however, the sparsity of the NBI is destroyed by a grid mismatch between NBI sources and SC-FDMA system. Towards this end, an accurate grid mismatch model is presented and a sparsifying transform is utilized to restore the sparsity of the unknown signal. Numerical results are presented that depict the suitability of the proposed scheme for NBI mitigation.
Implementation of LTE SC-FDMA on the USRP2 Software Defined Radio Platform
DEFF Research Database (Denmark)
Jørgensen, Peter Bjørn; Hansen, Thomas Lundgaard; Sørensen, Troels Bundgaard
2011-01-01
In this paper we discuss the implementation of a Single Carrier Frequency Division Multiple Access (SC-FDMA) transceiver running over the Universal Software Radio Peripheral 2 (USRP2). SC-FDMA is the air interface which has been selected for the uplink in the latest Long Term Evolution (LTE...
Improving SC-FDMA performance by Turbo Equalization in UTRA LTE Uplink
DEFF Research Database (Denmark)
Berardinelli, Gilberto; Priyanto, Basuki Endah; Sørensen, Troels Bundgaard
2008-01-01
of UTRA Long Term Evolution (LTE) Uplink. The performance is evaluated for 1x2 Single Input Multiple Output (SIMO) antenna configuration in a 6 paths Typical Urban (TU-06) channel profile. For assessment purpose, the results are compared with SC-FDMA MMSE and OFDMA schemes. Simulation results show...
Experimental and simulation analysis of the W-band SC-FDMA hybrid optical-wireless transmission
DEFF Research Database (Denmark)
Dogadaev, Anton Konstantinovich; Pang, Xiaodan; Deng, Lei
2014-01-01
We report on the experimental demonstration of the W-band hybrid optical-wireless SC-FDMA with 1.49 Gbit/s transmission over up to 2.3 m of air propagation. Provided simulation performance analysis proves a potential to reach 12.1 Gbit/s.......We report on the experimental demonstration of the W-band hybrid optical-wireless SC-FDMA with 1.49 Gbit/s transmission over up to 2.3 m of air propagation. Provided simulation performance analysis proves a potential to reach 12.1 Gbit/s....
Sum rates of asynchronous GFDMA and SC-FDMA for 5G uplink
Directory of Open Access Journals (Sweden)
Woojin Park
2015-12-01
Full Text Available The fifth generation (5G of mobile communication envisions ultralow latency less than 1 ms for radio interface. To this end, frameless asynchronous multiple access may be needed to allow users to transmit instantly without waiting for the next frame start. In this paper, generalized frequency division multiple-access (GFDMA, one of the promising multiple-access candidates for 5G mobile, is compared with the conventional single-carrier FDMA (SC-FDMA in terms of the uplink sum rate when both techniques are adapted for the asynchronous scenario. In particular, a waveform windowing technique is applied to both schemes to mitigate the inter-user interference due to non-zero out-of-band emission.
Linear optics based nanoscopy.
Gur, Aviram; Fixler, Dror; Micó, Vicente; Garcia, Javier; Zalevsky, Zeev
2010-10-11
Classically, optical systems are considered to have a fundamental resolution limit due to wave nature of light. This article presents a novel method for observing sub-wavelength features in a conventional optical microscope using linear optics. The operation principle is based on a random and time varying flow of nanoparticles moving in proximity to the inspected sample. Those particles excite the evanescent waves and couple them into harmonic waves. The sub-wavelength features are encoded and later on digitally decoded by proper image processing of a sequence of images. The achievable final resolution limit corresponds to the size of the nanoparticles. Experimental proof of principle validation of the technique is reported.
An Inquiry-Based Linear Algebra Class
Wang, Haohao; Posey, Lisa
2011-01-01
Linear algebra is a standard undergraduate mathematics course. This paper presents an overview of the design and implementation of an inquiry-based teaching material for the linear algebra course which emphasizes discovery learning, analytical thinking and individual creativity. The inquiry-based teaching material is designed to fit the needs of a…
Measurement-Based Linear Optics.
Alexander, Rafael N; Gabay, Natasha C; Rohde, Peter P; Menicucci, Nicolas C
2017-03-17
A major challenge in optical quantum processing is implementing large, stable interferometers. We offer a novel approach: virtual, measurement-based interferometers that are programed on the fly solely by the choice of homodyne measurement angles. The effects of finite squeezing are captured as uniform amplitude damping. We compare our proposal to existing (physical) interferometers and consider its performance for BosonSampling, which could demonstrate postclassical computational power in the near future. We prove its efficiency in time and squeezing (energy) in this setting.
Narrowband Interference Mitigation in SC-FDMA Using Bayesian Sparse Recovery
Ali, Anum
2016-09-29
This paper presents a novel narrowband interference (NBI) mitigation scheme for single carrier-frequency division multiple access systems. The proposed NBI cancellation scheme exploits the frequency-domain sparsity of the unknown signal and adopts a low complexity Bayesian sparse recovery procedure. At the transmitter, a few randomly chosen data locations are kept data free to sense the NBI signal at the receiver. Furthermore, it is noted that in practice, the sparsity of the NBI signal is destroyed by a grid mismatch between the NBI sources and the system under consideration. Toward this end, first, an accurate grid mismatch model is presented that is capable of assuming independent offsets for multiple NBI sources, and second, the sparsity of the unknown signal is restored prior to reconstruction using a sparsifying transform. To improve the spectral efficiency of the proposed scheme, a data-aided NBI recovery procedure is outlined that relies on adaptively selecting a subset of data-points and using them as additional measurements. Numerical results demonstrate the effectiveness of the proposed scheme for NBI mitigation.
LMS Based Adaptive Channel Estimation for LTE Uplink
Directory of Open Access Journals (Sweden)
Md. Masud Rana
2010-12-01
Full Text Available In this paper, a variable step size based least mean squares (LMS channel estimation (CE algorithm is presented for a single carrier frequency division multiple access(SC-FDMA system under the umbrella of the long term evolution (LTE. This unbiased CE method can automatically adapts the weighting coefficients on the channel condition. Therefore, it does not require knowledge of channel,and noise statistics. Furthermore, it uses a phase weighting scheme to eliminate the signal fluctuations due to noise and decision errors. Such approaches can guarantee the convergence towards the true channel coefficient. The mean and mean square behaviors of the proposed CE algorithm are also analyzed. With the help of theoretical analysis and simulation results, we prove that the proposed algorithm outperforms the existing algorithms in terms of mean square error (MSE and bit error rate (BER by more than around 2.5dB.
Linear Regression Based Real-Time Filtering
Directory of Open Access Journals (Sweden)
Misel Batmend
2013-01-01
Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.
Hippocampus Segmentation Based on Local Linear Mapping
Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin
2017-04-01
We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.
Flexure Based Linear and Rotary Bearings
Voellmer, George M. (Inventor)
2016-01-01
A flexure based linear bearing includes top and bottom parallel rigid plates; first and second flexures connecting the top and bottom plates and constraining exactly four degrees of freedom of relative motion of the plates, the four degrees of freedom being X and Y axis translation and rotation about the X and Y axes; and a strut connecting the top and bottom plates and further constraining exactly one degree of freedom of the plates, the one degree of freedom being one of Z axis translation and rotation about the Z axis.
Linear Temporal Logic-based Mission Planning
Directory of Open Access Journals (Sweden)
Anil Kumar
2016-06-01
Full Text Available In this paper, we describe the Linear Temporal Logic-based reactive motion planning. We address the problem of motion planning for mobile robots, wherein the goal specification of planning is given in complex environments. The desired task specification may consist of complex behaviors of the robot, including specifications for environment constraints, need of task optimality, obstacle avoidance, rescue specifications, surveillance specifications, safety specifications, etc. We use Linear Temporal Logic to give a representation for such complex task specification and constraints. The specifications are used by a verification engine to judge the feasibility and suitability of plans. The planner gives a motion strategy as output. Finally a controller is used to generate the desired trajectory to achieve such a goal. The approach is tested using simulations on the LTLMoP mission planning tool, operating over the Robot Operating System. Simulation results generated using high level planners and low level controllers work simultaneously for mission planning and controlling the physical behavior of the robot.
Linear encoder based low frequency inertial sensor
Directory of Open Access Journals (Sweden)
Collette Christophe
2015-01-01
Full Text Available For many applications, there is an increasing demand for low cost, high-resolution inertial sensors, which are capable of operating in harsh environments. Recently, a prototype of small optical inertial sensor has been built, using a Michelson interferometer. A resolution of 3 pm/√Hz has been obtained above 4 Hz using only low cost components. Compared to most state-of-the-art devices, this prototype did not contain any coil, which offers several important advantages, including a low thermal noise in the suspension and a full compatibility with magnetic environments (like particle collider. On the other hand, the Michelson is known to be tricky to tune, especially when one attempts to miniaturize the sensor. In this paper, we will propose a novel concept of inertial sensor, based on a linear encoder. Compared to the Michelson, the encoder is much more easy to mount, and the calibration more stable. The price to pay is a reduced resolution. In order to overcome this limitation, we amplify mechanically the relative motion between the support and the inertial mass. First results obtained with the new sensor will be discussed, and compared with the Michelson inertial sensor.
Brain extraction based on locally linear representation-based classification.
Huang, Meiyan; Yang, Wei; Jiang, Jun; Wu, Yao; Zhang, Yu; Chen, Wufan; Feng, Qianjin
2014-05-15
Brain extraction is an important procedure in brain image analysis. Although numerous brain extraction methods have been presented, enhancing brain extraction methods remains challenging because brain MRI images exhibit complex characteristics, such as anatomical variability and intensity differences across different sequences and scanners. To address this problem, we present a Locally Linear Representation-based Classification (LLRC) method for brain extraction. A novel classification framework is derived by introducing the locally linear representation to the classical classification model. Under this classification framework, a common label fusion approach can be considered as a special case and thoroughly interpreted. Locality is important to calculate fusion weights for LLRC; this factor is also considered to determine that Local Anchor Embedding is more applicable in solving locally linear coefficients compared with other linear representation approaches. Moreover, LLRC supplies a way to learn the optimal classification scores of the training samples in the dictionary to obtain accurate classification. The International Consortium for Brain Mapping and the Alzheimer's Disease Neuroimaging Initiative databases were used to build a training dataset containing 70 scans. To evaluate the proposed method, we used four publicly available datasets (IBSR1, IBSR2, LPBA40, and ADNI3T, with a total of 241 scans). Experimental results demonstrate that the proposed method outperforms the four common brain extraction methods (BET, BSE, GCUT, and ROBEX), and is comparable to the performance of BEaST, while being more accurate on some datasets compared with BEaST. Copyright © 2014 Elsevier Inc. All rights reserved.
Controller design approach based on linear programming.
Tanaka, Ryo; Shibasaki, Hiroki; Ogawa, Hiromitsu; Murakami, Takahiro; Ishida, Yoshihisa
2013-11-01
This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor. © 2013 ISA. Published by ISA. All rights reserved.
DEFF Research Database (Denmark)
Garde, Henrik
2018-01-01
. For a fair comparison, exact matrix characterizations are used when probing the monotonicity relations to avoid errors from numerical solution to PDEs and numerical integration. Using a special factorization of the Neumann-to-Dirichlet map also makes the non-linear method as fast as the linear method......Detecting inhomogeneities in the electrical conductivity is a special case of the inverse problem in electrical impedance tomography, that leads to fast direct reconstruction methods. One such method can, under reasonable assumptions, exactly characterize the inhomogeneities based on monotonicity...... properties of either the Neumann-to-Dirichlet map (non-linear) or its FrÃ©chet derivative (linear). We give a comparison of the non-linear and linear approach in the presence of measurement noise, and show numerically that the two methods give essentially the same reconstruction in the unit disk domain...
Linear peristaltic pump based on electromagnetic actuators
Directory of Open Access Journals (Sweden)
Maddoui Lotfi
2014-01-01
Full Text Available In this paper a study and design of a linear peristaltic pump are presented. A set of electromagnetic (solenoid actuators is used as the active tools to drag the liquid by crushing an elastic tube. The pump consists of six serially-connected electromagnetic actuators controlled via an electronic board. This may be considered as a simulated peristalsis action of intestines. The dynamic performances of the pump are investigated analytically and experimentally.
Piecewise Linear Model-Based Image Enhancement
Directory of Open Access Journals (Sweden)
Fabrizio Russo
2004-09-01
Full Text Available A novel technique for the sharpening of noisy images is presented. The proposed enhancement system adopts a simple piecewise linear (PWL function in order to sharpen the image edges and to reduce the noise. Such effects can easily be controlled by varying two parameters only. The noise sensitivity of the operator is further decreased by means of an additional filtering step, which resorts to a nonlinear model too. Results of computer simulations show that the proposed sharpening system is simple and effective. The application of the method to contrast enhancement of color images is also discussed.
Non-Linear and Linear Model Based Controller Design for Variable-Speed Wind Turbines
Energy Technology Data Exchange (ETDEWEB)
Hand, M. M. (National Renewable Energy Laboratory); Balas, M. J. (Department of Aerospace Engineering Sciences, University of Colorado)
1999-04-07
Variable-speed, horizontal axis wind turbines use blade-pitch control to meet specified objectives for three regions of operation. This paper focuses on controller design for the constant power production regime. A simple, rigid, non-linear turbine model was used to systematically perform trade-off studies between two performance metrics. Minimization of both the deviation of the rotor speed from the desired speed and the motion of the actuator is obtained through systematic selection of proportional-integral-derivative controller gain values. The gain design is performed using a non-linear turbine model and two linear models. The linear models differ only in selection of linearization point. The gain combinations resulting from design based upon each of the three models are similar. Performance under each of the three gain combinations is acceptable according to the metrics selected. The importance of operating point selection for linear models is illustrated. Because the simulation runs efficiently, the non-linear model provides the best gain design, but careful selection of the linearization point can produce acceptable gain designs from linear models.
Optimal trajectories based on linear equations
Carter, Thomas E.
1990-01-01
The Principal results of a recent theory of fuel optimal space trajectories for linear differential equations are presented. Both impulsive and bounded-thrust problems are treated. A new form of the Lawden Primer vector is found that is identical for both problems. For this reason, starting iteratives from the solution of the impulsive problem are highly effective in the solution of the two-point boundary-value problem associated with bounded thrust. These results were applied to the problem of fuel optimal maneuvers of a spacecraft near a satellite in circular orbit using the Clohessy-Wiltshire equations. For this case two-point boundary-value problems were solved using a microcomputer, and optimal trajectory shapes displayed. The results of this theory can also be applied if the satellite is in an arbitrary Keplerian orbit through the use of the Tschauner-Hempel equations. A new form of the solution of these equations has been found that is identical for elliptical, parabolic, and hyperbolic orbits except in the way that a certain integral is evaluated. For elliptical orbits this integral is evaluated through the use of the eccentric anomaly. An analogous evaluation is performed for hyperbolic orbits.
Implementation of neural network based non-linear predictive
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....
EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
Lian, Yao; Ge, Meng; Pan, Xian-Ming
2014-12-19
B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
Mining Distance-Based Outliers in Near Linear Time
National Aeronautics and Space Administration — Full title: Mining Distance-Based Outliers in Near Linear Time with Randomization and a Simple Pruning Rule Abstract: Defining outliers by their distance to...
Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis
Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel
2013-01-01
This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007
Implementation of neural network based non-linear predictive control
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1999-01-01
of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...
Optimal difference-based estimation for partially linear models
Zhou, Yuejin
2017-12-16
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
PC Based Linear Variable Differential Displacement Measurement Uses Optical Technique
Directory of Open Access Journals (Sweden)
Tapan Kumar MAITI
2007-07-01
Full Text Available PC based linear variable differential displacement (LVDD measurement with optical approach has been presented. The technique is a good blending of both hardware and software and is basically an alternative method of linear variable differential transformer (LVDT. A visual basic (VB programming is used for this PC based measurement. Here the voltage output and the displacement of the reflector can be studied and stored continuously. Theoretical predictions are supported by experimental results. This technique can be used for the measurement of some non-electrical parameters e.g. force, torque and liquid level etc.
Lifetime Prediction of IGBT Modules based on Linear Damage Accumulation
DEFF Research Database (Denmark)
Choi, Uimin; Blaabjerg, Frede; Ma, Ke
2017-01-01
In this paper, the lifetime prediction of power device modules based on the linear damage accumulation in conjunction with real mission profile assessment is studied. Four tests are performed under two superimposed power cycling conditions using an advanced power cycling test setup with 600 V, 30...
A Spreadsheet-Based, Matrix Formulation Linear Programming Lesson
DEFF Research Database (Denmark)
Harrod, Steven
2009-01-01
The article focuses on the spreadsheet-based, matrix formulation linear programming lesson. According to the article, it makes a higher level of theoretical mathematics approachable by a wide spectrum of students wherein many may not be decision sciences or quantitative methods majors. Moreover...
Laser-plasma-based linear collider using hollow plasma channels
Energy Technology Data Exchange (ETDEWEB)
Schroeder, C.B., E-mail: CBSchroeder@lbl.gov; Benedetti, C.; Esarey, E.; Leemans, W.P.
2016-09-01
A linear electron–positron collider based on laser-plasma accelerators using hollow plasma channels is considered. Laser propagation and energy depletion in the hollow channel is discussed, as well as the overall efficiency of the laser-plasma accelerator. Example parameters are presented for a 1-TeV and 3-TeV center-of-mass collider based on laser-plasma accelerators.
The generalized sidelobe canceller based on quaternion widely linear processing.
Tao, Jian-wu; Chang, Wen-xiu
2014-01-01
We investigate the problem of quaternion beamforming based on widely linear processing. First, a quaternion model of linear symmetric array with two-component electromagnetic (EM) vector sensors is presented. Based on array's quaternion model, we propose the general expression of a quaternion semiwidely linear (QSWL) beamformer. Unlike the complex widely linear beamformer, the QSWL beamformer is based on the simultaneous operation on the quaternion vector, which is composed of two jointly proper complex vectors, and its involution counterpart. Second, we propose a useful implementation of QSWL beamformer, that is, QSWL generalized sidelobe canceller (GSC), and derive the simple expressions of the weight vectors. The QSWL GSC consists of two-stage beamformers. By designing the weight vectors of two-stage beamformers, the interference is completely canceled in the output of QSWL GSC and the desired signal is not distorted. We derive the array's gain expression and analyze the performance of the QSWL GSC in the presence of one type of interference. The advantage of QSWL GSC is that the main beam can always point to the desired signal's direction and the robustness to DOA mismatch is improved. Finally, simulations are used to verify the performance of the proposed QSWL GSC.
The Generalized Sidelobe Canceller Based on Quaternion Widely Linear Processing
Directory of Open Access Journals (Sweden)
Jian-wu Tao
2014-01-01
Full Text Available We investigate the problem of quaternion beamforming based on widely linear processing. First, a quaternion model of linear symmetric array with two-component electromagnetic (EM vector sensors is presented. Based on array’s quaternion model, we propose the general expression of a quaternion semiwidely linear (QSWL beamformer. Unlike the complex widely linear beamformer, the QSWL beamformer is based on the simultaneous operation on the quaternion vector, which is composed of two jointly proper complex vectors, and its involution counterpart. Second, we propose a useful implementation of QSWL beamformer, that is, QSWL generalized sidelobe canceller (GSC, and derive the simple expressions of the weight vectors. The QSWL GSC consists of two-stage beamformers. By designing the weight vectors of two-stage beamformers, the interference is completely canceled in the output of QSWL GSC and the desired signal is not distorted. We derive the array’s gain expression and analyze the performance of the QSWL GSC in the presence of one type of interference. The advantage of QSWL GSC is that the main beam can always point to the desired signal’s direction and the robustness to DOA mismatch is improved. Finally, simulations are used to verify the performance of the proposed QSWL GSC.
Asymmetric radiation transfer based on linear light-matter interaction
Jia, Zi-xun; Shuai, Yong; Zhang, Jia-hui; Tan, He-ping
2017-11-01
In this paper, asymmetric radiation transfer based on linear light-matter interaction has been proposed. Two naturally different numerical methods, finite difference time domain (FDTD) and rigorous coupled wave analysis (RCWA), are utilized to verify that asymmetric radiation transfer can exist for linear plasmonic meta-material. The overall asymmetry has been introduced to evaluate bifacial transmission. Physics for the asymmetric optical responses have been understood via electromagnetic field distributions. Dispersion relation for surface plasmon polariton (SPP) and temporal coupled mode theory (TCMT) have been employed to verify the physics discussed in the paper. Geometric effects and the disappearing of asymmetric transmission have also been investigated. The results gained herein broaden the cognition of linear optical system, facilitate the design of novel energy harvesting device.
Negative base encoding in optical linear algebra processors
Perlee, C.; Casasent, D.
1986-01-01
In the digital multiplication by analog convolution algorithm, the bits of two encoded numbers are convolved to form the product of the two numbers in mixed binary representation; this output can be easily converted to binary. Attention is presently given to negative base encoding, treating base -2 initially, and then showing that the negative base system can be readily extended to any radix. In general, negative base encoding in optical linear algebra processors represents a more efficient technique than either sign magnitude or 2's complement encoding, when the additions of digitally encoded products are performed in parallel.
Train repathing in emergencies based on fuzzy linear programming.
Meng, Xuelei; Cui, Bingmou
2014-01-01
Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Applied Research of Enterprise Cost Control Based on Linear Programming
Directory of Open Access Journals (Sweden)
Yu Shuo
2015-01-01
This paper researches the enterprise cost control through the linear programming model, and analyzes the restriction factors of the labor of enterprise production, raw materials, processing equipment, sales price, and other factors affecting the enterprise income, so as to obtain an enterprise cost control model based on the linear programming. This model can calculate rational production mode in the case of limited resources, and acquire optimal enterprise income. The production guiding program and scheduling arrangement of the enterprise can be obtained through calculation results, so as to provide scientific and effective guidance for the enterprise production. This paper adds the sensitivity analysis in the linear programming model, so as to learn about the stability of the enterprise cost control model based on linear programming through the sensitivity analysis, and verify the rationality of the model, and indicate the direction for the enterprise cost control. The calculation results of the model can provide a certain reference for the enterprise planning in the market economy environment, which have strong reference and practical significance in terms of the enterprise cost control.
A family of quantization based piecewise linear filter networks
DEFF Research Database (Denmark)
Sørensen, John Aasted
1992-01-01
A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...
MEMS Based Pressure Sensors – Linearity and Sensitivity Issues
Directory of Open Access Journals (Sweden)
Jaspreet Singh
2008-04-01
Full Text Available This paper describes the various nonlinearities (NL encountered in the Si-based Piezoresistive pressure sensors. The effect of various factors like diaphragm thickness, diaphragm curvature, position of the piezoresistors etc. is analyzed taking anisotropy into account. Also, the effect of modified bending stiffness due to presence of oxide/nitride used for isolation between metal and diaphragm is studied from linearity point of view.
Graph-based linear scaling electronic structure theory.
Niklasson, Anders M N; Mniszewski, Susan M; Negre, Christian F A; Cawkwell, Marc J; Swart, Pieter J; Mohd-Yusof, Jamal; Germann, Timothy C; Wall, Michael E; Bock, Nicolas; Rubensson, Emanuel H; Djidjev, Hristo
2016-06-21
We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broad range of electronic structure methods and materials, including challenging systems such as biomolecules. The methodology combines well-controlled accuracy, low computational cost, and natural low-communication parallelism. This combination addresses substantial shortcomings of linear scaling electronic structure theory, in particular with respect to quantum-based molecular dynamics simulations.
Daylighting System Based on Novel Design of Linear Fresnel lens
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Thanh Tuan Pham
2017-10-01
Full Text Available In this paper, we present a design and optical simulation of a daylighting system using a novel design of linear Fresnel lens, which is constructed based on the conservation of optical path length and edge ray theorem. The linear Fresnel lens can achieve a high uniformity by using a new idea of design in which each groove of the lens distributes sunlight uniformly over the receiver so that the whole lens also uniformly distributes sunlight over the receiver. In this daylighting system, the novel design of linear Fresnel lens significantly improves the uniformity of collector and distributor. Therefore, it can help to improve the performance of the daylighting system. The structure of the linear Fresnel lenses is designed by using Matlab. Then, the structure of lenses is appreciated by ray tracing in LightToolsTM to find out the optimum lens shape. In addition, the simulation is performed by using LightToolsTM to estimate the efficiency of the daylighting system. The results show that the designed collector can achieve the efficiency of ~80% with the tolerance of ~0.60 and the concentration ratio of 340 times, while the designed distributor can reach a high uniformity of >90%.
PID controller design for trailer suspension based on linear model
Kushairi, S.; Omar, A. R.; Schmidt, R.; Isa, A. A. Mat; Hudha, K.; Azizan, M. A.
2015-05-01
A quarter of an active trailer suspension system having the characteristics of a double wishbone type was modeled as a complex multi-body dynamic system in MSC.ADAMS. Due to the complexity of the model, a linearized version is considered in this paper. A model reduction technique is applied to the linear model, resulting in a reduced-order model. Based on this simplified model, a Proportional-Integral-Derivative (PID) controller was designed in MATLAB/Simulink environment; primarily to reduce excessive roll motions and thus improving the ride comfort. Simulation results show that the output signal closely imitates the input signal in multiple cases - demonstrating the effectiveness of the controller.
Robust linear discriminant analysis with distance based estimators
Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina
2017-11-01
Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.
A comparative study of linear and region based diagrams
Directory of Open Access Journals (Sweden)
Björn Gottfried
2015-06-01
Full Text Available There are two categories of objects spatial information science investigates: actual objects and their spatial properties, such as in geography, and abstract objects which are employed metaphorically, as for visual languages. A prominent example of the latter are diagrams that model knowledge of some domain. Different aspects of diagrams are of interest, including their formal properties or how human users work with them, for example, with diagrams representing sets. The literature about diagrammatic systems for the representation of sets shows a dominance of region-based diagrams like Euler circles and Venn diagrams. The effectiveness of these diagrams, however, is limited because region-based diagrams become quite complex for more then three sets. By contrast, linear diagrams are not equally prevalent but enable the representation of a greater number of sets without getting cluttered. Cluttered diagrams exhibit inherent complexity due to overlapping objects, irrelevant details, or other reasons that impinge upon their legibility. This study contrasts both types of diagrammatic systems and investigates whether the performance of users differs for both kinds of diagrams. A significant difference can be shown regarding the number of diagrams that can be drawn within a fixed period of time and regarding the number of errors made. The results indicate that linear diagrams are more effective by being more restrictive and because region based diagrams show much clutter due to overlapping, coincident, and tangentially touching contours, as well as an overwhelming number of empty zones. Linear diagrams are less prone to errors and do not suffer from clutter.
submitter Linear encoder based low frequency inertial sensor
Hellegouarch, Sylvain; Artoos, Kurt; Lambert, Pierre; Collette, Christophe
2016-01-01
In this article, we present a novel concept of inertial sensor, based on a linear encoder. Compared to other interferometric sensors, the encoder is much more easy to mount, and the calibration more stable. A prototype has been built and validated experimentally by comparison with a commercial seismometer. It has a resolution of about 10 pm/√Hz. In order to further improve the resolution, two concepts of mechanical amplifiers have been studied and compared. One of them is shown to be extremely promising, provided that the amplifier does not stiffen the sensor.
Applied research of quantum information based on linear optics
Energy Technology Data Exchange (ETDEWEB)
Xu, Xiao-Ye
2016-08-01
This thesis reports on outstanding work in two main subfields of quantum information science: one involves the quantum measurement problem, and the other concerns quantum simulation. The thesis proposes using a polarization-based displaced Sagnac-type interferometer to achieve partial collapse measurement and its reversal, and presents the first experimental verification of the nonlocality of the partial collapse measurement and its reversal. All of the experiments are carried out in the linear optical system, one of the earliest experimental systems to employ quantum communication and quantum information processing. The thesis argues that quantum measurement can yield quantum entanglement recovery, which is demonstrated by using the frequency freedom to simulate the environment. Based on the weak measurement theory, the author proposes that white light can be used to precisely estimate phase, and effectively demonstrates that the imaginary part of the weak value can be introduced by means of weak measurement evolution. Lastly, a nine-order polarization-based displaced Sagnac-type interferometer employing bulk optics is constructed to perform quantum simulation of the Landau-Zener evolution, and by tuning the system Hamiltonian, the first experiment to research the Kibble-Zurek mechanism in non-equilibrium kinetics processes is carried out in the linear optical system.
Orthotropic ductile fracture criterion based on linear transformation
Yoon, J. W.; Zhang, S.; Stoughton, T. B.
2017-09-01
Accurate modelling of orthotropic ductile fracture is key to carry out reliable numerical prediction of rupture in plastic deformation of lightweight metals, such as ultra high strength steel, aluminum alloys, titanium alloys and magnesium alloys. Experiments are conducted for an aluminum alloy in shear, uniaxial tension, plane strain tension along the rolling direction, the diagonal direction and the transverse direction. Loading processes are recorded and fracture strain is measured by analysis of deformation with digital image correlation. First, isotropic fracture behavior is modeled by both linear model (Maximum Shear Stress (MSS) plus mean stress) and nonlinear model (Hosford yield function plus mean stress) considering different triaxiality conditions. It is observed that the mean stress model shows significant difference in the compression area compared to Mohr Coulomb-based normal stress model and a new isotropic model with the mean stress term shows a good correlation for AA 6k21. This approach is extended to an anisotropic ductile fracture criterion based on linear transformation. The anisotropic ductile fracture criterion is applied to model orthotropic fracture strain in shear, uniaxial tension and plane strain tension. The predicted anisotropy in ductile fracture is compared with experimental results for the verification of its accuracy. The comparison indicates that the proposed anisotropic ductile fracture criterion accurately models orthotropic ductile fracture in various loading conditions in shear, uniaxial tension and plane strain tension.
Linear Frequency Estimation Technique for Reducing Frequency Based Signals.
Woodbridge, Jonathan; Bui, Alex; Sarrafzadeh, Majid
2010-06-01
This paper presents a linear frequency estimation (LFE) technique for data reduction of frequency-based signals. LFE converts a signal to the frequency domain by utilizing the Fourier transform and estimates both the real and imaginary parts with a series of vectors much smaller than the original signal size. The estimation is accomplished by selecting optimal points from the frequency domain and interpolating data between these points with a first order approximation. The difficulty of such a problem lies in determining which points are most significant. LFE is unique in the fact that it is generic to a wide variety of frequency-based signals such as electromyography (EMG), voice, and electrocardiography (ECG). The only requirement is that spectral coefficients are spatially correlated. This paper presents the algorithm and results from both EMG and voice data. We complete the paper with a description of how this method can be applied to pattern types of recognition, signal indexing, and compression.
Locally linear constraint based optimization model for material decomposition
Wang, Qian; Zhu, Yining; Yu, Hengyong
2017-11-01
Dual spectral computed tomography (DSCT) has a superior material distinguishability than the conventional single spectral computed tomography (SSCT). However, the decomposition process is an illposed problem, which is sensitive to noise. Thus, the decomposed image quality is degraded, and the corresponding signal-to-noise ratio (SNR) is much lower than that of directly reconstructed image of SSCT. In this work, we establish a locally linear relationship between the decomposed results of DSCT and SSCT. Based on this constraint, we propose an optimization model for DSCT and develop an iterative method with image guided filtering. To further improve the image quality, we employ a preprocessing method based on the relative total variation regularization. Both numerical simulations and real experiments are performed, and the results confirm the effectiveness of our proposed approach.
Correlation-based linear discriminant classification for gene expression data.
Pan, M; Zhang, J
2017-01-23
Microarray gene expression technology provides a systematic approach to patient classification. However, microarray data pose a great computational challenge owing to their large dimensionality, small sample sizes, and potential correlations among genes. A recent study has shown that gene-gene correlations have a positive effect on the accuracy of classification models, in contrast to some previous results. In this study, a recently developed correlation-based classifier, the ensemble of random subspace (RS) Fisher linear discriminants (FLDs), was utilized. The impact of gene-gene correlations on the performance of this classifier and other classifiers was studied using simulated datasets and real datasets. A cross-validation framework was used to evaluate the performance of each classifier using the simulated datasets or real datasets, and misclassification rates (MRs) were computed. Using the simulated data, the average MRs of the correlation-based classifiers decreased as the correlations increased when there were more correlated genes. Using real data, the correlation-based classifiers outperformed the non-correlation-based classifiers, especially when the gene-gene correlations were high. The ensemble RS-FLD classifier is a potential state-of-the-art computational method. The correlation-based ensemble RS-FLD classifier was effective and benefited from gene-gene correlations, particularly when the correlations were high.
Profile-based short linear protein motif discovery
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Haslam Niall J
2012-05-01
Full Text Available Abstract Background Short linear protein motifs are attracting increasing attention as functionally independent sites, typically 3–10 amino acids in length that are enriched in disordered regions of proteins. Multiple methods have recently been proposed to discover over-represented motifs within a set of proteins based on simple regular expressions. Here, we extend these approaches to profile-based methods, which provide a richer motif representation. Results The profile motif discovery method MEME performed relatively poorly for motifs in disordered regions of proteins. However, when we applied evolutionary weighting to account for redundancy amongst homologous proteins, and masked out poorly conserved regions of disordered proteins, the performance of MEME is equivalent to that of regular expression methods. However, the two approaches returned different subsets within both a benchmark dataset, and a more realistic discovery dataset. Conclusions Profile-based motif discovery methods complement regular expression based methods. Whilst profile-based methods are computationally more intensive, they are likely to discover motifs currently overlooked by regular expression methods.
Nanoporous Carbide-Derived Carbon Material-Based Linear Actuators
Directory of Open Access Journals (Sweden)
Janno Torop
2009-12-01
Full Text Available Devices using electroactive polymer-supported carbon material can be exploited as alternatives to conventional electromechanical actuators in applications where electromechanical actuators have some serious deficiencies. One of the numerous examples is precise microactuators. In this paper, we show for first time the dilatometric effect in nanocomposite material actuators containing carbide-derived carbon (CDC and polytetrafluoroetylene polymer (PTFE. Transducers based on high surface area carbide-derived carbon electrode materials are suitable for short range displacement applications, because of the proportional actuation response to the charge inserted, and high Coulombic efficiency due to the EDL capacitance. The material is capable of developing stresses in the range of tens of N cm-2. The area of an actuator can be dozens of cm2, which means that forces above 100 N are achievable. The actuation mechanism is based on the interactions between the high-surface carbon and the ions of the electrolyte. Electrochemical evaluations of the four different actuators with linear (longitudinal action response are described. The actuator electrodes were made from two types of nanoporous TiC-derived carbons with surface area (SA of 1150 m2 g-1 and 1470 m2 g-1, respectively. Two kinds of electrolytes were used in actuators: 1.0 M tetraethylammonium tetrafluoroborate (TEABF4 solution in propylene carbonate and pure ionic liquid 1-ethyl-3-methylimidazolium trifluoromethanesulfonate (EMITf. It was found that CDC based actuators exhibit a linear movement of about 1% in the voltage range of 0.8 V to 3.0 V at DC. The actuators with EMITf electrolyte had about 70% larger movement compared to the specimen with TEABF4 electrolyte.
Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems
Directory of Open Access Journals (Sweden)
Tain-Sou Tsay
2014-01-01
Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.
Tumor classification based on orthogonal linear discriminant analysis.
Wang, Huiya; Zhang, Shanwen
2014-01-01
Gene expression profiles have great potential for accurate tumor diagnosis. It is expected to enable us to diagnose tumors precisely and systematically, and also bring the researchers of machine learning two challenges, the curse of dimensionality and the small sample size problems. We propose a manifold learning based dimensional reduction algorithm named orthogonal local discriminant embedding (O-LDE) and apply it to tumor classification. Comparing with the classical local discriminant embedding (LDE), O-LDE aims to obtain an orthogonal linear projection matrix by solving an optimization problem. After being projected into a low-dimensional subspace by O-LDE, the data points of the same class maintain their intrinsic neighbor relations, whereas the neighboring points of the different classes are far from each other. Experimental results on a public tumor dataset validate the effectiveness and feasibility of the proposed algorithm.
Linear regression-based feature selection for microarray data classification.
Abid Hasan, Md; Hasan, Md Kamrul; Abdul Mottalib, M
2015-01-01
Predicting the class of gene expression profiles helps improve the diagnosis and treatment of diseases. Analysing huge gene expression data otherwise known as microarray data is complicated due to its high dimensionality. Hence the traditional classifiers do not perform well where the number of features far exceeds the number of samples. A good set of features help classifiers to classify the dataset efficiently. Moreover, a manageable set of features is also desirable for the biologist for further analysis. In this paper, we have proposed a linear regression-based feature selection method for selecting discriminative features. Our main focus is to classify the dataset more accurately using less number of features than other traditional feature selection methods. Our method has been compared with several other methods and in almost every case the classification accuracy is higher using less number of features than the other popular feature selection methods.
Predicting flight delay based on multiple linear regression
Ding, Yi
2017-08-01
Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.
Design of experiments an introduction based on linear models
Morris, Max D
2011-01-01
IntroductionExample: rainfall and grassland Basic elements of an experimentExperiments and experiment-like studies Models and data analysisLinear Statistical ModelsLinear vector spaces Basic linear model The hat matrix, least-squares estimates, and design information matrixThe partitioned linear model The reduced normal equations Linear and quadratic forms Estimation and information Hypothesis testing and informationBlocking and informationCompletely Randomized DesignsIntroductionModels Matrix formulation Influence of design on estimation Influence of design on hypothesis testingRandomized Com
Locally linear embedding (LLE) for MRI based Alzheimer's disease classification.
Liu, Xin; Tosun, Duygu; Weiner, Michael W; Schuff, Norbert
2013-12-01
Modern machine learning algorithms are increasingly being used in neuroimaging studies, such as the prediction of Alzheimer's disease (AD) from structural MRI. However, finding a good representation for multivariate brain MRI features in which their essential structure is revealed and easily extractable has been difficult. We report a successful application of a machine learning framework that significantly improved the use of brain MRI for predictions. Specifically, we used the unsupervised learning algorithm of local linear embedding (LLE) to transform multivariate MRI data of regional brain volume and cortical thickness to a locally linear space with fewer dimensions, while also utilizing the global nonlinear data structure. The embedded brain features were then used to train a classifier for predicting future conversion to AD based on a baseline MRI. We tested the approach on 413 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had baseline MRI scans and complete clinical follow-ups over 3 years with the following diagnoses: cognitive normal (CN; n=137), stable mild cognitive impairment (s-MCI; n=93), MCI converters to AD (c-MCI, n=97), and AD (n=86). We found that classifications using embedded MRI features generally outperformed (pclassifications using the original features directly. Moreover, the improvement from LLE was not limited to a particular classifier but worked equally well for regularized logistic regressions, support vector machines, and linear discriminant analysis. Most strikingly, using LLE significantly improved (p=0.007) predictions of MCI subjects who converted to AD and those who remained stable (accuracy/sensitivity/specificity: =0.68/0.80/0.56). In contrast, predictions using the original features performed not better than by chance (accuracy/sensitivity/specificity: =0.56/0.65/0.46). In conclusion, LLE is a very effective tool for classification studies of AD using multivariate MRI data. The improvement in
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.
Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping
2015-07-06
Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.
Experience on a cryogenic linear mechanism based on superconducting levitation
Serrano-Tellez, Javier; Romera-Juarez, Fernando; González-de-María, David; Lamensans, Mikel; Argelaguet-Vilaseca, Heribert; Pérez-Díaz, José-Luis; Sánchez-Casarrubios, Juan; Díez-Jiménez, Efrén.; Valiente-Blanco, Ignacio
2012-09-01
The instrumentation of many space missions requires operation in cryogenic temperatures. In all the cases, the use of mechanisms in this environment is a matter of concern, especially when long lifetime is required. With the aim of removing lifetime concerns and to benefit from the cryogenic environment, a cryogenic contactless linear mechanism has been developed. It is based on the levitation of a permanent magnet over superconductor disks. The mechanism has been designed, built, and tested to assess the performances of such technology. The levitation system solves the mechanical contact problems due to cold-welding effects, material degradation by fatigue, wearing, backlash, lubrication...etc, at cryogenic temperatures. In fact, the lower is the temperature the better the superconductor levitation systems work. The mechanism provides a wide stroke (18mm) and high resolution motion (1μm), where position is controlled by changing the magnetic field of its environment using electric-magnets. During the motion, the moving part of the mechanism levitates supported by the magnetic interaction with the high temperature type II superconductors after reaching the superconductor state down to 90K. This paper describes the results of the complete levitation system development, including extensive cryogenic testing to measure optically the motion range, resolution, run-outs and rotations in order to characterize the levitation mechanism and to verify its performance in a cryogenic environment.
Linear Transformer Drivers for Z-pinch Based Propulsion
Adams, Robert; Seidler, William; Giddens, Patrick; Fabisinski, Leo; Cassibry, Jason
2017-01-01
The MSFC/UAH team has been developing of a novel power management and distribution system called a Linear Transformer Driver (LTD). LTD's hold the promise of dramatically reducing the required mass to drive a z-pinch by replacing the capacitor banks which constitute half the mass of the entire system. The MSFC?UAH tea, is developing this technology in hope of integrating it with the Pulsed Fission Fusion (PuFF) propulsion concept. High-Voltage pulsed power systems used for Z-Pinch experimentation have in the past largely been based on Marx Generators. Marx generators deliver the voltage and current required for the Z-Pinch, but suffer from two significant drawbacks when applied to a flight system: they are very massive, consisting of high-voltage capacitor banks insulated in oil-filled tanks and they do not lend themselves to rapid pulsing. The overall goal of Phase 2 is to demonstrate the construction of a higher voltage stack from a number of cavities each of the design proven in Phase 1 and to characterize and understand the techniques for designing the stack. The overall goal of Phase 3 is to demonstrate the feasibility of constructing a higher energy cavity from a number of smaller LTD stacks, to characterize and understand the way in which the constituent stacks combine, and to extend this demonstration LTD to serve as the basis for a 64 kJ pulse generator for Z-Pinch experiments.
Linear Temporal Logic (LTL) Based Monitoring of Smart Manufacturing Systems.
Heddy, Gerald; Huzaifa, Umer; Beling, Peter; Haimes, Yacov; Marvel, Jeremy; Weiss, Brian; LaViers, Amy
2015-01-01
The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of multiple system behaviors, or sequences of movement, that can achieve the same high-level tasks. Likewise, this vision presents unique challenges regarding the management of environmental variables in concert with discrete, logic-based programming. Overcoming these challenges requires targeted performance and health monitoring of both the logical controller and the physical components of the robotic system. Prognostics and health management (PHM) defines a field of techniques and methods that enable condition-monitoring, diagnostics, and prognostics of physical elements, functional processes, overall systems, etc. PHM is warranted in this effort given that the controller is vulnerable to program changes, which propagate in unexpected ways, logical runtime exceptions, sensor failure, and even bit rot. The physical component's health is affected by the wear and tear experienced by machines constantly in motion. The controller's source of faults is inherently discrete, while the latter occurs in a manner that builds up continuously over time. Such a disconnect poses unique challenges for PHM. This paper presents a robotic monitoring system that captures and resolves this disconnect. This effort leverages supervisory robotic control and model checking with linear temporal logic (LTL), presenting them as a novel monitoring system for PHM. This methodology has been demonstrated in a MATLAB-based simulator for an industry inspired use-case in the context of PHM. Future work will use the methodology to develop adaptive, intelligent control strategies to evenly distribute wear on the joints of the robotic arms, maximizing the life of the system.
Linear Temporal Logic (LTL) Based Monitoring of Smart Manufacturing Systems
Heddy, Gerald; Huzaifa, Umer; Beling, Peter; Haimes, Yacov; Marvel, Jeremy; Weiss, Brian; LaViers, Amy
2017-01-01
The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of multiple system behaviors, or sequences of movement, that can achieve the same high-level tasks. Likewise, this vision presents unique challenges regarding the management of environmental variables in concert with discrete, logic-based programming. Overcoming these challenges requires targeted performance and health monitoring of both the logical controller and the physical components of the robotic system. Prognostics and health management (PHM) defines a field of techniques and methods that enable condition-monitoring, diagnostics, and prognostics of physical elements, functional processes, overall systems, etc. PHM is warranted in this effort given that the controller is vulnerable to program changes, which propagate in unexpected ways, logical runtime exceptions, sensor failure, and even bit rot. The physical component’s health is affected by the wear and tear experienced by machines constantly in motion. The controller’s source of faults is inherently discrete, while the latter occurs in a manner that builds up continuously over time. Such a disconnect poses unique challenges for PHM. This paper presents a robotic monitoring system that captures and resolves this disconnect. This effort leverages supervisory robotic control and model checking with linear temporal logic (LTL), presenting them as a novel monitoring system for PHM. This methodology has been demonstrated in a MATLAB-based simulator for an industry inspired use-case in the context of PHM. Future work will use the methodology to develop adaptive, intelligent control strategies to evenly distribute wear on the joints of the robotic arms, maximizing the life of the system. PMID:28730154
Dosimetric comparison of linear accelerator-based stereotactic radiosurgery systems
Directory of Open Access Journals (Sweden)
Sharma S
2007-01-01
Full Text Available Stereotactic radiosurgery (SRS is a special radiotherapy technique used to irradiate intracranial lesions by 3-D arrangements of narrow photon beams eliminating the needs of invasive surgery. Three different tertiary collimators, namely BrainLab and Radionics circular cones and BrainLab micro multileaf collimator (mMLC, are used for linear accelerator-based SRS systems (X-Knife. Output factor (St, tissue maximum ratio (TMR and off axis ratio (OAR of these three SRS systems were measured using CC01 (Scanditronix/ Welhofer and Pinpoint (PTW cylindrical and Markus plane parallel ionization chambers as well as TLD and radiochromic film. Measurement results of CC01 and Pinpoint chambers were very close to each other which indicate that further reduction in volume and physical dimensions of cylindrical ionization chamber is not necessary for SRS/SRT dosimetry. Output factors of BrainLab and Radionics SRS cones were very close to each other while output factors of equivalent diameter mMLC field were different from SRS circular cones. TMR of the three SRS systems compared were very close to one another. OAR of Radionics cone and BrainLab mMLC were very close to each other, within 2%. However, OARs of BrainLab cone were found comparable to OARs of Radionics cone and BrainLab mMLC within maximum variation of 4%. In addition, user-measured similar data of other three mMLC X-Knives were compared with the mMLC X-Knife data measured in this work and found comparable. The concept of switching over to mMLC-based SRS/SRT is thus validated from dosimetric characteristics as well.
A VBA-based Simulation for Teaching Simple Linear Regression
Jones, Gregory Todd; Hagtvedt, Reidar; Jones, Kari
2004-01-01
In spite of the name, simple linear regression presents a number of conceptual difficulties, particularly for introductory students. This article describes a simulation tool that provides a hands-on method for illuminating the relationship between parameters and sample statistics.
Partially Flipped Linear Algebra: A Team-Based Approach
Carney, Debra; Ormes, Nicholas; Swanson, Rebecca
2015-01-01
In this article we describe a partially flipped Introductory Linear Algebra course developed by three faculty members at two different universities. We give motivation for our partially flipped design and describe our implementation in detail. Two main features of our course design are team-developed preview videos and related in-class activities.…
Quantum-dot-based integrated non-linear sources
DEFF Research Database (Denmark)
Bernard, Alice; Mariani, Silvia; Andronico, Alessio
2015-01-01
The authors report on the design and the preliminary characterisation of two active non-linear sources in the terahertz and near-infrared range. The former is associated to difference-frequency generation between whispering gallery modes of an AlGaAs microring resonator, whereas the latter...
Hyperchaotic encryption based on multi-scroll piecewise linear Systems
Czech Academy of Sciences Publication Activity Database
García-Martínez, M.; Ontanon-García, L.J.; Campos-Cantón, E.; Čelikovský, Sergej
2015-01-01
Roč. 270, č. 1 (2015), s. 413-424 ISSN 0096-3003 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Hyperchaotic encryption * Piecewise linear systems * Stream cipher * Pseudo-random bit generator * Chaos theory * Multi-scrollattractors Subject RIV: BC - Control Systems Theory Impact factor: 1.345, year: 2015 http://library.utia.cas.cz/separaty/2015/TR/celikovsky-0446895.pdf
Operator-based Linearization for Modeling of Low-enthalpy Geothermal Processes
Khait, M.; Voskov, D.V.
2016-01-01
Simulation of geothermal processes is based on the solution of strongly nonlinear governing equations describing flow of mass and energy in the subsurface. The solution of this problem requires a linearization of governing equations. Recently, a new approach based on the operator-based multi-linear
Optical-tweezing-based linear-optics nanoscopy.
Wagner, Omer; Schultz, Moty; Ramon, Yonatan; Sloutskin, Eli; Zalevsky, Zeev
2016-04-18
Previous works reported that linear optics could be used to observe sub-wavelength features with a conventional optical microscope. Yet, the ability to reach a sub-200 nm resolution with a visible light remains limited. We present a novel widely-applicable method, where particle trapping is employed to overcome this limit. The combination of the light scattered by the sample and by the trapped particles encodes super-resolution information, which we decode by post image processing, with the trapped particle locations predetermined. As the first proof of concept our method successfully resolved sample characteristic features down to 100 nm. Improved performance is achieved with the fluorescence of the trapped particles employed. Further improvement may be attained with trapped particles of a smaller size.
Optimization techniques for OpenCL-based linear algebra routines
Kozacik, Stephen; Fox, Paul; Humphrey, John; Kuller, Aryeh; Kelmelis, Eric; Prather, Dennis W.
2014-06-01
The OpenCL standard for general-purpose parallel programming allows a developer to target highly parallel computations towards graphics processing units (GPUs), CPUs, co-processing devices, and field programmable gate arrays (FPGAs). The computationally intense domains of linear algebra and image processing have shown significant speedups when implemented in the OpenCL environment. A major benefit of OpenCL is that a routine written for one device can be run across many different devices and architectures; however, a kernel optimized for one device may not exhibit high performance when executed on a different device. For this reason kernels must typically be hand-optimized for every target device family. Due to the large number of parameters that can affect performance, hand tuning for every possible device is impractical and often produces suboptimal results. For this work, we focused on optimizing the general matrix multiplication routine. General matrix multiplication is used as a building block for many linear algebra routines and often comprises a large portion of the run-time. Prior work has shown this routine to be a good candidate for high-performance implementation in OpenCL. We selected several candidate algorithms from the literature that are suitable for parameterization. We then developed parameterized kernels implementing these algorithms using only portable OpenCL features. Our implementation queries device information supplied by the OpenCL runtime and utilizes this as well as user input to generate a search space that satisfies device and algorithmic constraints. Preliminary results from our work confirm that optimizations are not portable from one device to the next, and show the benefits of automatic tuning. Using a standard set of tuning parameters seen in the literature for the NVIDIA Fermi architecture achieves a performance of 1.6 TFLOPS on an AMD 7970 device, while automatically tuning achieves a peak of 2.7 TFLOPS
Equivalent Linearization Analysis Method for Base-isolated Buildings
Liu, Tao
2014-01-01
Base isolation system, as one of the most popular means to mitigate the seismic risks, often exhibits strong nonlinearity. To simplify the procedure of structural design, bilinear force-deformation behavior is recommended for isolation systems in most modern structural codes. Although base isolation system can be analyzed through nonlinear time history method, solving of a system with a large number of degrees of freedom may require an exorbitant amount of time. As a substitute, the equiva...
Observer-based linear parameter varying H∞ tracking control for hypersonic vehicles
Directory of Open Access Journals (Sweden)
Yiqing Huang
2016-11-01
Full Text Available This article aims to develop observer-based linear parameter varying output feedback H∞ tracking controller for hypersonic vehicles. Due to the complexity of an original nonlinear model of the hypersonic vehicle dynamics, a slow–fast loop linear parameter varying polytopic model is introduced for system stability analysis and controller design. Then, a state observer is developed by linear parameter varying technique in order to estimate the unmeasured attitude angular for slow loop system. Also, based on the designed linear parameter varying state observer, a kind of attitude tracking controller is presented to reduce tracking errors for all bounded reference attitude angular inputs. The closed-loop linear parameter varying system is proved to be quadratically stable by Lypapunov function technique. Finally, simulation results show that the developed linear parameter varying H∞ controller has good tracking capability for reference commands.
Dynamic Model Based Vector Control of Linear Induction Motor
2012-05-01
sensorless control is critical for LIM control in some special case. Reference [13] introduces a direct torque and flux control based on space...Industry Applications, IEEE Transactions on, vol. 28, no. 5, pp. 1054–1061, 1992. [4] J. Nash, “ Direct torque control , induction motor vector ...13] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” Industry Applications,
Linear feature selection in texture analysis - A PLS based method
DEFF Research Database (Denmark)
Marques, Joselene; Igel, Christian; Lillholm, Martin
2013-01-01
We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... sets. The texture analysis framework was applied to diagnosis of knee osteoarthritis (OA). To classify between healthy subjects and OA patients, a generic bank of texture features was extracted from magnetic resonance images of tibial knee bone. The features were used as input to the DR algorithm...
Operator-based Linearization for Modeling of Low-enthalpy Geothermal Processes
Khait, M.; Voskov, D.V.
2016-01-01
Simulation of geothermal processes is based on the solution of strongly nonlinear governing equations describing flow of mass and energy in the subsurface. The solution of this problem requires a linearization of governing equations. Recently, a new approach based on the operator-based multi-linear representation of conservation equations was proposed for an isothermal flow and transport. The discretized version of conservation equations was transformed to the operator form where each term of...
Fiber grating sensing interrogation based on an InGaAs photodiode linear array.
Li, Guoyu; Guo, Tuan; Zhang, Hao; Gao, Hongwei; Zhang, Jian; Liu, Bo; Yuan, Shuzhong; Kai, Guiyun; Dong, Xiaoyi
2007-01-20
We present a new method of the fiber grating sensing interrogation technique by utilizing an indium gallium arsenide photodiode linear array and blazed fiber Bragg gratings. An interrogation system based on an InGaAs photodiode linear array is designed, and the system performance is analyzed. The interrogation system shows a good prospect for smart sensing.
Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood
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.
Directory of Open Access Journals (Sweden)
A. V. Sidorenko
2015-01-01
Full Text Available In this paper we assessed the sustainability of the encryption algorithm based on dynamic chaos, as well as the basic principles for the implementation of linear and differential cryptanalysis.
Approach to the implementation of linear-assisted-based battery chargers
Directory of Open Access Journals (Sweden)
Martínez-García Herminio
2017-01-01
Full Text Available This article shows the proposal of a linear-assisted regulator or linear-&-switching hybrid regulator with a constant switching frequency. The control loop of the system is based on the current-mode technique. The main disadvantage of a regulator with current-mode control is the inherent instability of the loop when switch duty ratios are greater than 0.5. In order to make stable the proposed linear-assisted regulator, the article shows the technique based on a slope compensation. This kind of voltage regulators is especially devoted to battery chargers in renewable energy systems.
Linear VSS and Distributed Commitments Based on Secret Sharing and Pairwise Checks
DEFF Research Database (Denmark)
Fehr, Serge; Maurer, Ueli M.
2002-01-01
. VSS and DC are main building blocks for unconditional secure multi-party computation protocols. This general approach covers all known linear VSS and DC schemes. The main theorem states that the security of a scheme is equivalent to a pure linear-algebra condition on the linear mappings (e.......g. described as matrices and vectors) describing the scheme. The security of all known schemes follows as corollaries whose proofs are pure linear-algebra arguments, in contrast to some hybrid arguments used in the literature. Our approach is demonstrated for the CDM DC scheme, which we generalize to be secure......We present a general treatment of all non-cryptographic (i.e., information-theoretically secure) linear veriable-secret-sharing (VSS) and distributed-commitment (DC) schemes, based on an underlying secret sharing scheme, pairwise checks between players, complaints, and accusations of the dealer...
Geometric Correction of Airborne Linear Array Image Based on Bias Matrix
Wang, M.; Hu, J.; Zhou, M.; Li, J. M.; Zhang, Z.
2013-05-01
As the linear array sensor has great potential in disaster monitoring, geological survey, the quality of the image geometric correction should be guaranteed. The primary focus of this paper is to present a new method correcting airbone linear image based on the bias matrix,which is bulit by describing and analysing the errors of airbone linear image included the misalignment. The bias matrix was considered as additional observations to the traditional geometric correction model in our method. And by using control points which have both image coordinate and object coordinate, the solving equation from geometric correction model can be established and the bias matrix can be calculated by adjustment strategy. To avoid the singularity problem in the calculating process, this paper uses quaternion to describe the image's attitude and rotation instead of traditional calculating method which is structured by the Euler angle. Finally, geometric correction of airborne linear array image with high accuracy based on bias matrix can be achieved.
PCR-based detection of a rare linear DNA in cell culture
Directory of Open Access Journals (Sweden)
Saveliev Sergei V.
2002-01-01
Full Text Available The described method allows for detection of rare linear DNA fragments generated during genomic deletions. The predicted limit of the detection is one DNA molecule per 107 or more cells. The method is based on anchor PCR and involves gel separation of the linear DNA fragment and chromosomal DNA before amplification. The detailed chemical structure of the ends of the linear DNA can be defined with the use of additional PCR-based protocols. The method was applied to study the short-lived linear DNA generated during programmed genomic deletions in a ciliate. It can be useful in studies of spontaneous DNA deletions in cell culture or for tracking intracellular modifications at the ends of transfected DNA during gene therapy trials.
Massimiliano Ferraioli; Alberto Mandara
2016-01-01
Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation ...
Design of Linear CMOS Transconductance Elements for Alpha-Power Law Based MOSFETs
Bhaskar Gopalan
2015-01-01
A model on alpha-power law MOSFETs based source-coupled differential pair (SCDP) is discussed and a simple design procedure for realizing a linear CMOS SCDP transconductance element is proposed. The modified SCDP circuit using this procedure is an alternative to that of conventional SCDP and the circuit discussed has superior linearity than the conventional SCDP for a wide range of input differential voltage. The modified SCDP also includes the circuitry needed to suppress the variation in th...
A novel approach based on preference-based index for interval bilevel linear programming problem.
Ren, Aihong; Wang, Yuping; Xue, Xingsi
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes
Vogl, Gregory W.; Weiss, Brian A.; Donmez, M. Alkan
2017-01-01
A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality. PMID:28691039
Lin, Chao; Shen, Xueju; Wang, Zhisong; Zhao, Cheng
2014-06-20
We demonstrate a novel optical asymmetric cryptosystem based on the principle of elliptical polarized light linear truncation and a numerical reconstruction technique. The device of an array of linear polarizers is introduced to achieve linear truncation on the spatially resolved elliptical polarization distribution during image encryption. This encoding process can be characterized as confusion-based optical cryptography that involves no Fourier lens and diffusion operation. Based on the Jones matrix formalism, the intensity transmittance for this truncation is deduced to perform elliptical polarized light reconstruction based on two intensity measurements. Use of a quick response code makes the proposed cryptosystem practical, with versatile key sensitivity and fault tolerance. Both simulation and preliminary experimental results that support theoretical analysis are presented. An analysis of the resistance of the proposed method on a known public key attack is also provided.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
Directory of Open Access Journals (Sweden)
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Noiseless Linear Amplifiers in Entanglement-Based Continuous-Variable Quantum Key Distribution
Directory of Open Access Journals (Sweden)
Yichen Zhang
2015-06-01
Full Text Available We propose a method to improve the performance of two entanglement-based continuous-variable quantum key distribution protocols using noiseless linear amplifiers. The two entanglement-based schemes consist of an entanglement distribution protocol with an untrusted source and an entanglement swapping protocol with an untrusted relay. Simulation results show that the noiseless linear amplifiers can improve the performance of these two protocols, in terms of maximal transmission distances, when we consider small amounts of entanglement, as typical in realistic setups.
Larom, Bar; Nazarathy, Moshe; Rudnitsky, Arkady; Nevet, Amir; Zalevsky, Zeev
2010-06-21
Feasibility of cascading and reconfiguring a pair of linear-nonlinear all-optical logic gate structures is experimentally demonstrated using RF photonics. Progress in highly integrated O/E/O repeaters over Si/InP hybrid platforms enables large-scale reconfigurable gate arrays.
The Control of Asymmetric Rolling Missiles Based on Improved Trajectory Linearization Control Method
Directory of Open Access Journals (Sweden)
Huadong Sun
2016-07-01
Full Text Available According to motion characteristic of an asymmetric rolling missile with damage fin, a three-channel controlled model is established. The controller which is used to realize non-linear tracking and decoupling control of the roll and angle motion is introduced based on an improved trajector y linearization control method. The improved method is composed of the classic trajectory linearization control method and a compensation control law. The classic trajectory linearization control method is implemented in the time-scale separation principle. The Lipschitz non-linear state observer systematically obtained by solving the linear matrix inequality approach is provided to estimate state variables and unknown parameters, and then the compensation control law utilizing the estimated unknown parameters improves the TLC method. Simulation experiments show that the adaptive decoupling control ensure tracking performance, and the robustness and accuracy of missile attitude control are ensured under the condition of the system parameters uncertainty, random observation noise and external disturbance caused by damage fin.
Energy Technology Data Exchange (ETDEWEB)
Mjalli, F.S.; Al-Asheh, S. [Chemical Engineering Department, Qatar University, Doha (Qatar)
2005-10-01
In this work advanced nonlinear neural networks based control system design algorithms are adopted to control a mechanistic model for an ethanol fermentation process. The process model equations for such systems are highly nonlinear. A neural network strategy has been implemented in this work for capturing the dynamics of the mechanistic model for the fermentation process. The neural network achieved has been validated against the mechanistic model. Two neural network based nonlinear control strategies have also been adopted using the model identified. The performance of the feedback linearization technique was compared to neural network model predictive control in terms of stability and set point tracking capabilities. Under servo conditions, the feedback linearization algorithm gave comparable tracking and stability. The feedback linearization controller achieved the control target faster than the model predictive one but with vigorous and sudden controller moves. (Abstract Copyright [2005], Wiley Periodicals, Inc.)
Electro-Optic Swept Source Based on AOTF for Wavenumber-Linear Interferometric Sensing and Imaging
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Ga-Hee Han
2016-04-01
Full Text Available We demonstrate a novel electro-optic swept source for wavenumber-linear interferometric sensing and imaging applications. The electro-optic swept source based on an acousto-optic tunable filter (AOTF provides high environmental stability and arbitrary drive function sweeping because the electro-optic wavelength selection does not depend on a mechanical moving component to tune the output lasing wavelength. We show improved stability of the suggested electro-optic swept source, compared to a conventional swept source based on a fiber Fabry–Perot tunable filter (FFP-TF. Various types of wavelength sweeping are demonstrated by applying the programmed drive function to the applied radio frequency (RF of the AOTF. We demonstrated improved image quality of optical coherence tomography (OCT by using the wavenumber-linear drive function of a simple triangular signal, which has a high wavenumber-linearity with an R-square value of 0.99991.
Application of wavelet-based multiple linear regression model to rainfall forecasting in Australia
He, X.; Guan, H.; Zhang, X.; Simmons, C.
2013-12-01
In this study, a wavelet-based multiple linear regression model is applied to forecast monthly rainfall in Australia by using monthly historical rainfall data and climate indices as inputs. The wavelet-based model is constructed by incorporating the multi-resolution analysis (MRA) with the discrete wavelet transform and multiple linear regression (MLR) model. The standardized monthly rainfall anomaly and large-scale climate index time series are decomposed using MRA into a certain number of component subseries at different temporal scales. The hierarchical lag relationship between the rainfall anomaly and each potential predictor is identified by cross correlation analysis with a lag time of at least one month at different temporal scales. The components of predictor variables with known lag times are then screened with a stepwise linear regression algorithm to be selectively included into the final forecast model. The MRA-based rainfall forecasting method is examined with 255 stations over Australia, and compared to the traditional multiple linear regression model based on the original time series. The models are trained with data from the 1959-1995 period and then tested in the 1996-2008 period for each station. The performance is compared with observed rainfall values, and evaluated by common statistics of relative absolute error and correlation coefficient. The results show that the wavelet-based regression model provides considerably more accurate monthly rainfall forecasts for all of the selected stations over Australia than the traditional regression model.
Linear and volumetric dimensional changes of injection-molded PMMA denture base resins.
El Bahra, Shadi; Ludwig, Klaus; Samran, Abdulaziz; Freitag-Wolf, Sandra; Kern, Matthias
2013-11-01
The aim of this study was to evaluate the linear and volumetric dimensional changes of six denture base resins processed by their corresponding injection-molding systems at 3 time intervals of water storage. Two heat-curing (SR Ivocap Hi Impact and Lucitone 199) and four auto-curing (IvoBase Hybrid, IvoBase Hi Impact, PalaXpress, and Futura Gen) acrylic resins were used with their specific injection-molding technique to fabricate 6 specimens of each material. Linear and volumetric dimensional changes were determined by means of a digital caliper and an electronic hydrostatic balance, respectively, after water storage of 1, 30, or 90 days. Means and standard deviations of linear and volumetric dimensional changes were calculated in percentage (%). Statistical analysis was done using Student's and Welch's t tests with Bonferroni-Holm correction for multiple comparisons (α=0.05). Statistically significant differences in linear dimensional changes between resins were demonstrated at all three time intervals of water immersion (p≤0.05), with exception of the following comparisons which showed no significant difference: IvoBase Hi Impact/SR Ivocap Hi Impact and PalaXpress/Lucitone 199 after 1 day, Futura Gen/PalaXpress and PalaXpress/Lucitone 199 after 30 days, and IvoBase Hybrid/IvoBase Hi Impact after 90 days. Also, statistically significant differences in volumetric dimensional changes between resins were found at all three time intervals of water immersion (p≤0.05), with exception of the comparison between PalaXpress and Futura Gen. Denture base resins (IvoBase Hybrid and IvoBase Hi Impact) processed by the new injection-molding system (IvoBase), revealed superior dimensional precision. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Linear algebra-based matrix structural analysis of two-dimensional reciprocal structures
DEFF Research Database (Denmark)
Parigi, Dario
2017-01-01
The following paper proposes a formulation for the extension of linear algebra-based matrix structural analysis to assemblies in which elements join in intermediate points. Such a formulation in particular must include now the possibility to describe an expanded set of joints as prismatic joint...
Knill-laflamme-milburn linear optics quantum computation as a measurement-based computation.
Popescu, Sandu
2007-12-21
We show that the Knill Lafllame Milburn method of quantum computation with linear optics gates can be interpreted as a one-way, measurement-based quantum computation of the type introduced by Briegel and Raussendorf. We also show that the permanent state of n n-dimensional systems is a universal state for quantum computation.
Mat-Rix-Toe: Improving Writing through a Game-Based Project in Linear Algebra
Graham-Squire, Adam; Farnell, Elin; Stockton, Julianna Connelly
2014-01-01
The Mat-Rix-Toe project utilizes a matrix-based game to deepen students' understanding of linear algebra concepts and strengthen students' ability to express themselves mathematically. The project was administered in three classes using slightly different approaches, each of which included some editing component to encourage the…
A Modified Approach to Team-Based Learning in Linear Algebra Courses
Nanes, Kalman M.
2014-01-01
This paper documents the author's adaptation of team-based learning (TBL), an active learning pedagogy developed by Larry Michaelsen and others, in the linear algebra classroom. The paper discusses the standard components of TBL and the necessary changes to those components for the needs of the course in question. There is also an empirically…
An Example of Competence-Based Learning: Use of Maxima in Linear Algebra for Engineers
Diaz, Ana; Garcia, Alfonsa; de la Villa, Agustin
2011-01-01
This paper analyses the role of Computer Algebra Systems (CAS) in a model of learning based on competences. The proposal is an e-learning model Linear Algebra course for Engineering, which includes the use of a CAS (Maxima) and focuses on problem solving. A reference model has been taken from the Spanish Open University. The proper use of CAS is…
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.
A dual framework for lower bounds of the quadratic assignment|problem based on linearization
DEFF Research Database (Denmark)
Karisch, Stefan E.; Cela, E.; Clausen, Jens
1999-01-01
A dual framework allowing the comparison of various bounds for the quadratic assignment problem (QAP) based on linearization, e.g. the bounds of Adams and Johnson, Carraresi and Malucelli, and Hahn and Grant, is presented. We discuss the differences of these bounds and propose a new and more...
Zhang, Hao; Zou, Weiwen; Chen, Jianping
2015-03-15
We propose a method to generate a widely tunable linearly chirped microwave waveform based on spectral filtering and unbalanced dispersion. Heterodyne beating between two differently dispersed optical pulses in a photodetector produces the linearly chirped microwave waveform. Desired waveforms with flexible and independent control of the center frequency and sweep bandwidth can be obtained by simply tuning two optical filters. Simulation and experimental investigations are carried out, and the results are in good agreement. The measured microwave waveform has ∼5.2-ns pulse duration and ∼64-GHz sweep bandwidth, corresponding to a time-bandwidth product of ∼166.4 and a compression ratio of ∼248.
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.
Choi, Jae-Seok; Kim, Munchurl
2017-03-01
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower
Directory of Open Access Journals (Sweden)
Jia Chaolong
2013-01-01
Full Text Available Good track geometry state ensures the safe operation of the railway passenger service and freight service. Railway transportation plays an important role in the Chinese economic and social development. This paper studies track irregularity standard deviation time series data and focuses on the characteristics and trend changes of track state by applying clustering analysis. Linear recursive model and linear-ARMA model based on wavelet decomposition reconstruction are proposed, and all they offer supports for the safe management of railway transportation.
Guo, Sangang
2017-09-01
There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.
Dang, Qianyu; Mazumdar, Sati; Houck, Patricia R
2008-08-01
The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effects. Using GLIMMIX based on these linearization methods, we derived formulas for power and sample size calculations for longitudinal designs with attrition over time. We found that the power and sample size estimates depend on the within-subject correlation and the size of random effects. In this article, we present tables of minimum sample sizes commonly used to test hypotheses for longitudinal studies. A simulation study was used to compare the results. We also provide a Web link to the SAS macro that we developed to compute power and sample sizes for correlated binary outcomes.
Directory of Open Access Journals (Sweden)
Yubo Wang
2017-06-01
Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
Wang, Yubo; Veluvolu, Kalyana C
2017-06-14
It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
2D non-separable linear canonical transform (2D-NS-LCT) based cryptography
Zhao, Liang; Muniraj, Inbarasan; Healy, John J.; Malallah, Ra'ed; Cui, Xiao-Guang; Ryle, James P.; Sheridan, John T.
2017-05-01
The 2D non-separable linear canonical transform (2D-NS-LCT) can describe a variety of paraxial optical systems. Digital algorithms to numerically evaluate the 2D-NS-LCTs are not only important in modeling the light field propagations but also of interest in various signal processing based applications, for instance optical encryption. Therefore, in this paper, for the first time, a 2D-NS-LCT based optical Double-random- Phase-Encryption (DRPE) system is proposed which offers encrypting information in multiple degrees of freedom. Compared with the traditional systems, i.e. (i) Fourier transform (FT); (ii) Fresnel transform (FST); (iii) Fractional Fourier transform (FRT); and (iv) Linear Canonical transform (LCT), based DRPE systems, the proposed system is more secure and robust as it encrypts the data with more degrees of freedom with an augmented key-space.
Machine learning-based methods for prediction of linear B-cell epitopes.
Wang, Hsin-Wei; Pai, Tun-Wen
2014-01-01
B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.
Directory of Open Access Journals (Sweden)
Massimiliano Ferraioli
2016-01-01
Full Text Available Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation bearings supporting the adjacent structures. In this situation, the conventional equivalent linear elastic analysis may have some problems of accuracy because this method is calibrated on single base-isolated structures. Moreover, the torsional characteristics of the combined system are significantly different from those of separate isolated buildings. A number of numerical simulations and parametric studies under earthquake excitations were performed. The accuracy of the dynamic response obtained by the equivalent linear elastic model was calculated by the magnitude of the error with respect to the corresponding response considering the nonlinear behaviour of the isolation system. The maximum displacements at the isolation level, the maximum interstorey drifts, and the peak absolute acceleration were selected as the most important response measures. The influence of mass eccentricity, torsion, and high-modes effects was finally investigated.
Huang, Desheng; Quan, Yu; He, Miao; Zhou, Baosen
2009-12-10
More studies based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification methods. The main purpose of this research was to compare the performance of linear discriminant analysis (LDA) and its modification methods for the classification of cancer based on gene expression data. The classification performance of linear discriminant analysis (LDA) and its modification methods was evaluated by applying these methods to six public cancer gene expression datasets. These methods included linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), shrinkage centroid regularized discriminant analysis (SCRDA), shrinkage linear discriminant analysis (SLDA) and shrinkage diagonal discriminant analysis (SDDA). The procedures were performed by software R 2.80. PAM picked out fewer feature genes than other methods from most datasets except from Brain dataset. For the two methods of shrinkage discriminant analysis, SLDA selected more genes than SDDA from most datasets except from 2-class lung cancer dataset. When comparing SLDA with SCRDA, SLDA selected more genes than SCRDA from 2-class lung cancer, SRBCT and Brain dataset, the result was opposite for the rest datasets. The average test error of LDA modification methods was lower than LDA method. The classification performance of LDA modification methods was superior to that of traditional LDA with respect to the average error and there was no significant difference between theses modification methods.
Li, Kunpeng
2017-01-01
The compatibility problem between rapidity and overshooting in the traditional predictive current control structure is inevitable and difficult to solve by reason of using PI controller. A novel predictive current control (PCC) algorithm for permanent magnet synchronous motor (PMSM) based on linear active disturbance rejection control (LADRC) is presented in this paper. In order to displace PI controller, the LADRC strategy which consisted of linear state error feedback (LSEF) control algorithm and linear extended state observer (LESO), is designed based on the mathematic model of PMSM. The purpose of LSEF is to make sure fast response to load mutation and system uncertainties, and LESO is designed to estimate the uncertain disturbances. The principal structures of the proposed system are speed outer loop based on LADRC and current inner loop based on predictive current control. Especially, the instruction value of qaxis current in inner loop is derived from the control quantity which is designed in speed outer loop. The simulation is carried out in Matlab/Simulink software, and the results illustrate that the dynamic and static performances of proposed system are satisfied. Moreover the robust against model parameters mismatch is enhanced obviously.
Directory of Open Access Journals (Sweden)
Farman Ali Mangi
2016-01-01
Full Text Available A multiband circular polarizer based on fission transmission of linearly polarized wave for x-band application is proposed, which is constructed of 2 × 2 metallic strips array. The linear-to-circular polarization conversion is obtained by decomposing the linearly incident x-polarized wave into two orthogonal vector components of equal amplitude and 90° phase difference between them. The innovative approach of “fission transmission of linear-to-circular polarized wave” is firstly introduced to obtain giant circular dichroism based on decomposition of orthogonal vector components through the structure. It means that the incident linearly polarized wave is converted into two orthogonal components through lower printed metallic strips layer and two transmitted waves impinge on the upper printed strips layer to convert into four orthogonal vector components at the end of structure. This projection and transmission sequence of orthogonal components sustain the chain transmission of electromagnetic wave and can achieve giant circular dichroism. Theoretical analysis and microwave experiments are presented to validate the performance of the structure. The measured results are in good agreement with simulation results. In addition, the proposed circular polarizer exhibits the optimal performance with respect to the normal incidence. The right handed circularly polarized wave is emitted ranging from 10.08 GHz to 10.53 GHz and 10.78 GHz to 11.12 GHz, while the left handed circular polarized wave is excited at 10.54 GHz–10.70 GHz and 11.13 GHz–11.14 GHz, respectively.
Huang, Congzhi; Sira-Ramírez, Hebertt
2015-12-01
A flatness-based active disturbance rejection control approach is proposed to deal with the linear systems with unknown time-varying coefficients and external disturbances. By selecting appropriate nominal values for the parameters of the system, all the deviation between the nominal and actual dynamics of the controlled process, as well as all the external disturbances can be viewed as a total disturbance. Based on the accurately estimated total disturbance with the aid of the proposed extended state observer, a linear proportional derivative feedback control law taking into account the derivatives of the desired output is designed to eliminate the effect of the total disturbance on the system performance. Finally, the load frequency control problem of a single-area power system with non-reheated unit is employed as an illustrative example to demonstrate the effectiveness of the proposed approach.
Linear GPR Imaging Based on Electromagnetic Plane-Wave Spectra and Diffraction Tomography
DEFF Research Database (Denmark)
Meincke, Peter
2004-01-01
Two linear diffraction-tomography based inversion schemes, referred to as the Fourier transform method (FTM) and the far-field method (FFM), are derived for 3-dimensional fixed-offset GPR imaging of buried objects. The FTM and FFM are obtained by using different asymptotic approximations in the f......Two linear diffraction-tomography based inversion schemes, referred to as the Fourier transform method (FTM) and the far-field method (FFM), are derived for 3-dimensional fixed-offset GPR imaging of buried objects. The FTM and FFM are obtained by using different asymptotic approximations...... in the forward model. The two inversion schemes include an accurate electromagnetic description of the GPR antennas through their plane-wave transmitting and receiving spectra. The performance of the FTM is investigated through a numerical example involving a 2.5-dimensional configuration in which the GPR...
Mover Position Detection for PMTLM Based on Linear Hall Sensors through EKF Processing.
Yan, Leyang; Zhang, Hui; Ye, Peiqing
2017-04-06
Accurate mover position is vital for a permanent magnet tubular linear motor (PMTLM) control system. In this paper, two linear Hall sensors are utilized to detect the mover position. However, Hall sensor signals contain third-order harmonics, creating errors in mover position detection. To filter out the third-order harmonics, a signal processing method based on the extended Kalman filter (EKF) is presented. The limitation of conventional processing method is first analyzed, and then EKF is adopted to detect the mover position. In the EKF model, the amplitude of the fundamental component and the percentage of the harmonic component are taken as state variables, and they can be estimated based solely on the measured sensor signals. Then, the harmonic component can be calculated and eliminated. The proposed method has the advantages of faster convergence, better stability and higher accuracy. Finally, experimental results validate the effectiveness and superiority of the proposed method.
Feedback Linearization Based Arc Length Control for Gas Metal Arc Welding
DEFF Research Database (Denmark)
Thomsen, Jesper Sandberg
2005-01-01
In this paper a feedback linearization based arc length controller for gas metal arc welding (GMAW) is described. A nonlinear model describing the dynamic arc length is transformed into a system where nonlinearities can be cancelled by a nonlinear state feedback control part, and thus, leaving only......, the cancellation of nonlinear terms might give rise to problems with respect to robustness. Robustness of the closed loop system is therefore nvestigated by simulation....
Analysis of VCO based noise shaping ADCs linearized by PWM modulation
Hernandez , Luis; Prefasi, , Enrique; Paton , Susana; Rombouts, Pieter
2012-01-01
Nonlinearity is one of the main problems associated with VCO based noise shaping ADCs. Their open loop architecture does not permit correction of the nonlinear voltage to frequency response of the VCO by feedback. Recently, linearization of a VCO ADC by Pulse Width Modulation (PWM) precoding has been proposed. Here, the input signal is encoded by a PWM modulator to drive the VCO with a 2-level signal, thus eliminating the nonlinearity of the VCO. This paper analyzes the remaining inherent dis...
Linear coherent receiver based on a broadband and sampling optical phase-locked loop
DEFF Research Database (Denmark)
Bowers, J.E.; Ramaswamy, A.; Johansson, L.A.
2007-01-01
A novel coherent receiver for linear optical phase demodulation is proposed and experimentally demonstrated. The receiver, based on a broadband optical phase-lock loop has a bandwidth of 1.45 GHz. Using the receiver in an analog link experiment, a spurious free dynamic range of 125 dBHz2....../3 is measured at 300 MHz. Further, theoretical investigations are presented demonstrating receiver operation at high frequencies (>2 GHz) using a sampling phase-locked loop....
Directory of Open Access Journals (Sweden)
Ousmane Coulibaly
2016-01-01
Full Text Available We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the solar declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Pô and 3.65% (Dédougou. The maximum value of the RMSD which is 312.36 kJ/m2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
Cogging force rejection method of linear motor based on internal model principle
Liu, Yang; Chen, Zhenyu; Yang, Tianbo
2015-02-01
The cogging force disturbance of linear motor is one of the main factors affecting the positioning accuracy of ultraprecision moving platform. And this drawback could not be completely overcome by improving the design of motor body, such as location modification of permanent magnet array, or optimization design of the shape of teeth-slot. So the active compensation algorithms become prevalent in cogging force rejection area. This paper proposed a control structure based on internal mode principle to attenuate the cogging force of linear motor which deteriorated the accuracy of position, and this structure could make tracking and anti-disturbing performance of close-loop designed respectively. In the first place, the cogging force was seen as the intrinsic property of linear motor and its model constituting controlled object with motor ontology model was obtained by data driven recursive identification method. Then, a control structure was designed to accommodate tracking and anti-interference ability separately by using internal model principle. Finally, the proposed method was verified in a long stroke moving platform driven by linear motor. The experiment results show that, by employing this control strategy, the positioning error caused by cogging force was decreased by 70%.
Local Ray-Based Traveltime Computation Using the Linearized Eikonal Equation
Almubarak, Mohammed S.
2013-05-01
The computation of traveltimes plays a critical role in the conventional implementations of Kirchhoff migration. Finite-difference-based methods are considered one of the most effective approaches for traveltime calculations and are therefore widely used. However, these eikonal solvers are mainly used to obtain early-arrival traveltime. Ray tracing can be used to pick later traveltime branches, besides the early arrivals, which may lead to an improvement in velocity estimation or in seismic imaging. In this thesis, I improved the accuracy of the solution of the linearized eikonal equation by constructing a linear system of equations (LSE) based on finite-difference approximation, which is of second-order accuracy. The ill-conditioned LSE is initially regularized and subsequently solved to calculate the traveltime update. Numerical tests proved that this method is as accurate as the second-order eikonal solver. Later arrivals are picked using ray tracing. These traveltimes are binned to the nearest node on a regular grid and empty nodes are estimated by interpolating the known values. The resulting traveltime field is used as an input to the linearized eikonal algorithm, which improves the accuracy of the interpolated nodes and yields a local ray-based traveltime. This is a preliminary study and further investigation is required to test the efficiency and the convergence of the solutions.
Schmerling, Edward; Janson, Lucas; Pavone, Marco
2015-12-01
In this paper we provide a thorough, rigorous theoretical framework to assess optimality guarantees of sampling-based algorithms for drift control systems: systems that, loosely speaking, can not stop instantaneously due to momentum. We exploit this framework to design and analyze a sampling-based algorithm (the Differential Fast Marching Tree algorithm) that is asymptotically optimal, that is, it is guaranteed to converge, as the number of samples increases, to an optimal solution. In addition, our approach allows us to provide concrete bounds on the rate of this convergence. The focus of this paper is on mixed time/control energy cost functions and on linear affine dynamical systems, which encompass a range of models of interest to applications (e.g., double-integrators) and represent a necessary step to design, via successive linearization, sampling-based and provably-correct algorithms for non-linear drift control systems. Our analysis relies on an original perturbation analysis for two-point boundary value problems, which could be of independent interest.
A Neural Network Based Hybrid Mixture Model to Extract Information from Non-linear Mixed Pixels
Directory of Open Access Journals (Sweden)
Uttam Kumar
2012-09-01
Full Text Available Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember’s (pure pixel’s distribution. This communication discusses inferring class fraction through a novel hybrid mixture model (HMM. HMM is a three-step process, where the endmembers are first derived from the images themselves using the N-FINDR algorithm. These endmembers are used by the linear mixture model (LMM in the second step that provides an abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual ground proportions are fed into neural network based multi-layer perceptron (MLP architecture as input to train the neurons. The neural output further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. HMM is first implemented and validated on simulated hyper spectral data of 200 bands and subsequently on real time MODIS data with a spatial resolution of 250 m. The results on computer simulated data show that the method gives acceptable results for unmixing pixels with an overall RMSE of 0.0089 ± 0.0022 with LMM and 0.0030 ± 0.0001 with the HMM when compared to actual class proportions. The unmixed MODIS images showed overall RMSE with HMM as 0.0191 ± 0.022 as compared to the LMM output considered alone that had an overall RMSE of 0.2005 ± 0.41, indicating that individual class abundances obtained from HMM are very close to the real observations.
Designing a graph-based approach to landscape ecological assessment of linear infrastructures
Energy Technology Data Exchange (ETDEWEB)
Girardet, Xavier, E-mail: xavier.girardet@univ-fcomte.fr; Foltête, Jean-Christophe, E-mail: jean-christophe.foltete@univ-fcomte.fr; Clauzel, Céline, E-mail: celine.clauzel@univ-fcomte.fr
2013-09-15
The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact.
TreeEFM: calculating elementary flux modes using linear optimization in a tree-based algorithm.
Pey, Jon; Villar, Juan A; Tobalina, Luis; Rezola, Alberto; García, José Manuel; Beasley, John E; Planes, Francisco J
2015-03-15
Elementary flux modes (EFMs) analysis constitutes a fundamental tool in systems biology. However, the efficient calculation of EFMs in genome-scale metabolic networks (GSMNs) is still a challenge. We present a novel algorithm that uses a linear programming-based tree search and efficiently enumerates a subset of EFMs in GSMNs. Our approach is compared with the EFMEvolver approach, demonstrating a significant improvement in computation time. We also validate the usefulness of our new approach by studying the acetate overflow metabolism in the Escherichia coli bacteria. To do so, we computed 1 million EFMs for each energetic amino acid and then analysed the relevance of each energetic amino acid based on gene/protein expression data and the obtained EFMs. We found good agreement between previous experiments and the conclusions reached using EFMs. Finally, we also analysed the performance of our approach when applied to large GSMNs. The stand-alone software TreeEFM is implemented in C++ and interacts with the open-source linear solver COIN-OR Linear program Solver (CLP). © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Shao, Xingling; Wang, Honglun
2015-01-01
This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Singh, H P; Sukavanam, N
2012-01-01
This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709-14] is presented. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Xiaoyi Wang
2015-01-01
Full Text Available In wastewater treatment plants (WWTPs, the dissolved oxygen is the key variable to be controlled in bioreactors. In this paper, linear active disturbance rejection control (LADRC is utilized to track the dissolved oxygen concentration based on benchmark simulation model number 1 (BSM1. Optimal LADRC parameters tuning approach for wastewater treatment processes is obtained by analyzing and simulations on BSM1. Moreover, by analyzing the estimation capacity of linear extended state observer (LESO in the control of dissolved oxygen, the parameter range of LESO is acquired, which is a valuable guidance for parameter tuning in simulation and even in practice. The simulation results show that LADRC can overcome the disturbance existing in the control of wastewater and improve the tracking accuracy of dissolved oxygen. LADRC provides another practical solution to the control of WWTPs.
Development of a web-based simulator for estimating motion errors in linear motion stages
Khim, G.; Oh, J.-S.; Park, C.-H.
2017-08-01
This paper presents a web-based simulator for estimating 5-DOF motion errors in the linear motion stages. The main calculation modules of the simulator are stored on the server computer. The clients uses the client software to send the input parameters to the server and receive the computed results from the server. By using the simulator, we can predict performances such as 5-DOF motion errors, bearing and table stiffness by entering the design parameters in a design step before fabricating the stages. Motion errors are calculated using the transfer function method from the rail form errors which is the most dominant factor on the motion errors. To verify the simulator, the predicted motion errors are compared to the actually measured motion errors in the linear motion stage.
Self-consistent field theory based molecular dynamics with linear system-size scaling
Energy Technology Data Exchange (ETDEWEB)
Richters, Dorothee [Institute of Mathematics and Center for Computational Sciences, Johannes Gutenberg University Mainz, Staudinger Weg 9, D-55128 Mainz (Germany); Kühne, Thomas D., E-mail: kuehne@uni-mainz.de [Institute of Physical Chemistry and Center for Computational Sciences, Johannes Gutenberg University Mainz, Staudinger Weg 7, D-55128 Mainz (Germany); Technical and Macromolecular Chemistry, University of Paderborn, Warburger Str. 100, D-33098 Paderborn (Germany)
2014-04-07
We present an improved field-theoretic approach to the grand-canonical potential suitable for linear scaling molecular dynamics simulations using forces from self-consistent electronic structure calculations. It is based on an exact decomposition of the grand canonical potential for independent fermions and does neither rely on the ability to localize the orbitals nor that the Hamilton operator is well-conditioned. Hence, this scheme enables highly accurate all-electron linear scaling calculations even for metallic systems. The inherent energy drift of Born-Oppenheimer molecular dynamics simulations, arising from an incomplete convergence of the self-consistent field cycle, is circumvented by means of a properly modified Langevin equation. The predictive power of the present approach is illustrated using the example of liquid methane under extreme conditions.
Locally Linear Diffeomorphic Metric Embedding (LLDME) for surface-based anatomical shape modeling.
Yang, Xianfeng; Goh, Alvina; Qiu, Anqi
2011-05-01
This paper presents the algorithm, Locally Linear Diffeomorphic Metric Embedding (LLDME), for constructing efficient and compact representations of surface-based brain shapes whose variations are characterized using Large Deformation Diffeomorphic Metric Mapping (LDDMM). Our hypothesis is that the shape variations in the infinite-dimensional diffeomorphic metric space can be captured by a low-dimensional space. To do so, traditional Locally Linear Embedding (LLE) that reconstructs a data point from its neighbors in Euclidean space is extended to LLDME that requires interpolating a shape from its neighbors in the infinite-dimensional diffeomorphic metric space. This is made possible through the conservation law of momentum derived from LDDMM. It indicates that initial momentum, a linear transformation of the initial velocity of diffeomorphic flows, at a fixed template shape determines the geodesic connecting the template to a subject's shape in the diffeomorphic metric space and becomes the shape signature of an individual subject. This leads to the compact linear representation of the nonlinear diffeomorphisms in terms of the initial momentum. Since the initial momentum is in a linear space, a shape can be approximated by a linear combination of its neighbors in the diffeomorphic metric space. In addition, we provide efficient computations for the metric distance between two shapes through the first order approximation of the geodesic using the initial momentum as well as for the reconstruction of a shape given its low-dimensional Euclidean coordinates using the geodesic shooting with the initial momentum as the initial condition. Experiments are performed on the hippocampal shapes of 302 normal subjects across the whole life span (18-94years). Compared with Principal Component Analysis and ISOMAP, LLDME provides the most compact and efficient representation of the age-related hippocampal shapes. Even though the hippocampal volumes among young adults are as
Designing Backstepping Control System for Hypersonic Vehicle Based on Feedback Linearization
Directory of Open Access Journals (Sweden)
Jianli Wei
2015-01-01
Full Text Available A hypersonic vehicle uses the airbreathing scramjet engine and the airframe and engine integrated design. Therefore, there is a strong cross-coupling effect among its aerodynamic force, thrust, structure, and control. The nonlinearity and uncertainty of the model cause difficulties in control system design. Considering the nonlinearity, coupling characteristics, and aerodynamic parametric uncertainty of its longitudinal dynamic model, we design the control law for its altitude system and velocity system based on the adaptive backstepping control method. Because of the feedback linearization method, we introduce the constraints of the flight vehicle’s actuator into the design, obtaining the robust adaptive control system constrained by the actuator of the flight vehicle. To avoid the high-order derivation problem of the feedback linearization method and the derivation of the virtual control volume in adaptive backstepping control method, we use the arbitrary-order robust exact differentiator to solve the high-order derivatives in feedback linearization and utilize the command filter to obtain the virtual control volume and its derivatives. The simulation results show that the robust adaptive control system we designed can achieve the error-free tracking of altitude and velocity command. It can well overcome the influence of structural parameters, aerodynamic parametric uncertainty, and disturbances; meanwhile, the control command can satisfy the constraints of the actuator.
Protograph based LDPC codes with minimum distance linearly growing with block size
Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy
2005-01-01
We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.
Aneesh, R; Khijwania, Sunil K
2011-09-20
The main objective of the present work is to develop an optical fiber relative humidity (RH) sensor having a linear response throughout over the widest possible dynamic range. We report an optical fiber RH sensor based on the evanescent wave absorption spectroscopy that fulfills this objective. The fiber sensor employs a specific nanoparticle (zinc oxide) doped sol-gel nanostructured sensing film of optimum thickness, synthesized over a short length of a centrally decladded straight and uniform optical fiber. A detailed experimental investigation is carried out to analyze the sensor response/characteristics. Fiber sensor response is observed to be linear throughout the dynamic range as wide as 4% to 96% RH. The observed linear sensitivity for the fiber sensor is 0.0012 RH(-1). The average response time of the reported sensor is observed to be as short as 0.06 s during the humidification. In addition, the sensor exhibited a very good degree of reversibility and extremely high reliability as well as repeatability.
A tool for semi-automatic linear feature detection based on DTM
Bonetto, Sabrina; Facello, Anna; Ferrero, Anna Maria; Umili, Gessica
2015-02-01
The tectonic movement along faults is often reflected by geomorphological features such as linear valleys, ridgelines and slope-breaks, steep slopes of uniform aspect, regional anisotropy and tilt of terrain. In the last years, remote sensing data have been used as a source of information for the detection of tectonic structures. In this paper, a new fully 3D approach for semi-automatic extraction and characterization of geological lineaments is presented: linear features are detected on a DTM by means of algorithms based on principal curvature values, and then they are grouped according to data collected from literature review regarding expected orientation of lineaments in the studied area. The overall positive aspects of this semi-automatic process were found to be the informativeness on geological structure for preliminary geological assessment and set identification, the possibility to identify the most interesting portions to be investigated and to analyze zones that are not directly accessible. This method has been applied to a geologically well-known area (the Monferrato geological domain) in order to validate the results of the software processing with remotely sensed data collected from literature review. As regard to orientation, spatial distribution and length of the lineaments, the study demonstrates a correspondence of the obtained results with both remote sensed linear features and field geostructural data.
Directory of Open Access Journals (Sweden)
Shi Jun
2015-02-01
Full Text Available Downward-looking Linear Array Synthetic Aperture Radar (LASAR has many potential applications in the topographic mapping, disaster monitoring and reconnaissance applications, especially in the mountainous area. However, limited by the sizes of platforms, its resolution in the linear array direction is always far lower than those in the range and azimuth directions. This disadvantage leads to the blurring of Three-Dimensional (3D images in the linear array direction, and restricts the application of LASAR. To date, the research on 3D SAR image enhancement has focused on the sparse recovery technique. In this case, the one-to-one mapping of Digital Elevation Model (DEM brakes down. To overcome this, an optimal DEM reconstruction method for LASAR based on the variational model is discussed in an effort to optimize the DEM and the associated scattering coefficient map, and to minimize the Mean Square Error (MSE. Using simulation experiments, it is found that the variational model is more suitable for DEM enhancement applications to all kinds of terrains compared with the Orthogonal Matching Pursuit (OMPand Least Absolute Shrinkage and Selection Operator (LASSO methods.
Robert, Philippe; Violas, Xavier; Grand, Sylvie; Lehericy, Stéphane; Idée, Jean-Marc; Ballet, Sébastien; Corot, Claire
2016-01-01
Objectives The aim of this study was to evaluate Gd retention in the deep cerebellar nuclei (DCN) of linear gadolinium-based contrast agents (GBCAs) compared with a macrocyclic contrast agent. Materials and Methods The brain tissue retention of Gd of 3 linear GBCAs (gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide) and a macrocyclic GBCA (gadoterate meglumine) was compared in healthy rats (n = 8 per group) that received 20 intravenous injections of 0.6 mmol Gd/kg (4 injections per week for 5 weeks). An additional control group with saline was included. T1-weighted magnetic resonance imaging was performed before injection and once a week during the 5 weeks of injections and for another 4 additional weeks after contrast period. Total gadolinium concentration was measured with inductively coupled plasma mass spectrometry. Blinded qualitative and quantitative evaluations of the T1 signal intensity in DCN were performed, as well as a statistical analysis on quantitative data. Results At completion of the injection period, all the linear contrast agents (gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide) induced a significant increase in signal intensity in DCN, unlike the macrocyclic GBCA (gadoterate meglumine) or saline. The T1 hypersignal enhancement kinetic was fast for gadodiamide. Total Gd concentrations for the 3 linear GBCAs groups at week 10 were significantly higher in the cerebellum (1.21 ± 0.48, 1.67 ± 0.17, and 3.75 ± 0.18 nmol/g for gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide, respectively) than with the gadoterate meglumine (0.27 ± 0.16 nmol/g, P dimeglumine, and gadopentetate dimeglumine to healthy rats were associated with progressive and significant T1 signal hyperintensity in the DCN, along with Gd deposition in the cerebellum. This is in contrast with the macrocyclic GBCA gadoterate meglumine for which no effect was observed. PMID:26606549
Ravva, Patanjali; Karlsson, Mats O; French, Jonathan L
2014-04-30
The application of model-based meta-analysis in drug development has gained prominence recently, particularly for characterizing dose-response relationships and quantifying treatment effect sizes of competitor drugs. The models are typically nonlinear in nature and involve covariates to explain the heterogeneity in summary-level literature (or aggregate data (AD)). Inferring individual patient-level relationships from these nonlinear meta-analysis models leads to aggregation bias. Individual patient-level data (IPD) are indeed required to characterize patient-level relationships but too often this information is limited. Since combined analyses of AD and IPD allow advantage of the information they share to be taken, the models developed for AD must be derived from IPD models; in the case of linear models, the solution is a closed form, while for nonlinear models, closed form solutions do not exist. Here, we propose a linearization method based on a second order Taylor series approximation for fitting models to AD alone or combined AD and IPD. The application of this method is illustrated by an analysis of a continuous landmark endpoint, i.e., change from baseline in HbA1c at week 12, from 18 clinical trials evaluating the effects of DPP-4 inhibitors on hyperglycemia in diabetic patients. The performance of this method is demonstrated by a simulation study where the effects of varying the degree of nonlinearity and of heterogeneity in covariates (as assessed by the ratio of between-trial to within-trial variability) were studied. A dose-response relationship using an Emax model with linear and nonlinear effects of covariates on the emax parameter was used to simulate data. The simulation results showed that when an IPD model is simply used for modeling AD, the bias in the emax parameter estimate increased noticeably with an increasing degree of nonlinearity in the model, with respect to covariates. When using an appropriately derived AD model, the linearization
Shojiguchi, A.; Tanaka, T.; Okada, M.
Recently a modified algorithm of code-division multiple-access (CDMA) parallel interference canceler (PIC) has been proposed by Tanaka based on statistical neurodynamics. In this paper we apply the modified algorithm to the linear PIC (LPIC) and investigate its stability. We show that the stable (unstable) fixed points of the modified algorithm correspond to the stable (unstable) replica symmetry solutions with the Gaussian prior. We also show the modified algorithm is a special case of Kabashima's belief-propagation algorithm with Gaussian prior.
Simplified non-linear time-history analysis based on the Theory of Plasticity
DEFF Research Database (Denmark)
Costa, Joao Domingues
2005-01-01
is based on the Theory of Plasticity. Firstly, the formulation and the computational procedure to perform time-history analysis of a rigid-plastic single degree of freedom (SDOF) system are presented. The necessary conditions for the method to incorporate pinching as well as strength degradation......This paper aims at giving a contribution to the problem of developing simplified non-linear time-history (NLTH) analysis of structures which dynamical response is mainly governed by plastic deformations, able to provide designers with sufficiently accurate results. The method to be presented...
System Reliability of Timber Trusses Based on Non-Linear Structural Modelling
DEFF Research Database (Denmark)
Hansson, Martin; Ellegaard, Peter
2006-01-01
. In this paper, Monte Carlo simulations of a timber W-truss with punched metal plate fasteners (nail plates) are performed. Structural timber displays a significant variability in strength and stiffness both within and between members and is described by a statistic model calibrated against data from Norway...... spruce (Picea abies). Most studies found in the literature are based on linear-elastic theory and the variability within members is neglected mainly because of lack of data. The FE calculations are performed by TrussLab - a toolbox for MATLAB developed at Aalborg University. TrussLab considers contact...
The Design of Ship Autopilot by Applying Observer - Based Feedback Linearization
Directory of Open Access Journals (Sweden)
Zwierzewicz Zenon
2015-01-01
Full Text Available The paper considers the problem of ship autopilot design based on Bech’s model of the vessel. Since the model is highly nonlinear and some of the state vector coordinates are unavailable, the control system synthesis is performed by means of an output feedback linearization method combined with a nonlinear observer. The asymptotic stability of the overall system has been proven, including the asymptotic stability of the system internal dynamics. The performed simulations of the ship course-changing process have confirmed a high performance of the proposed controller. It has been emphasized that for its practical usability the system robustification is necessary.
Pulse generators based on air-insulated linear-transformer-driver stages
Directory of Open Access Journals (Sweden)
B. M. Kovalchuk
2013-05-01
Full Text Available In this paper we present the design and test results of pulse generators based on air-insulated linear-transformer-driver stages that drive a vacuum transmission line. A custom designed unit, referred to as a capacitor block, was developed for use as a main structural element of the transformer stages. It incorporates two capacitors GA 35426 (40 nF, 100 kV and a multichannel multigap gas switch. Two types of stages were developed: (1 stage LTD-20 with four modules in parallel and five capacitor blocks in each module (in tests of this stage current amplitude up to 850 kA with ∼140 ns rise time was obtained on a 0.05 Ω load at 100 kV charging voltage; (2 stage LTD-4 with two modules in parallel and two capacitor blocks in each module. Several installations were built on the base of these stages, including a linear transformer, consisting of two identical LTD-20 stages in series, and a high power electron accelerator on the base of LTD-4 stages. The design, tests results, and main problems are presented and discussed in this paper for these installations.
Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G
2012-03-01
Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (Plinear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Compensation of Linear Multiscale Doppler for OFDM-Based Underwater Acoustic Communication Systems
Directory of Open Access Journals (Sweden)
A. E. Abdelkareem
2012-01-01
Full Text Available In particular cases, such as acceleration, it is required to design a receiver structure that is capable of accomplishing time varying Doppler compensation. In this paper, two approaches are taken into consideration in order to estimate the symbol timing offset parameter. The first method employed to achieve an estimate of this particular parameter is based upon centroid localization and this prediction is reinforced by a second technique which utilises linear prediction, based on the assumption that the speed changes linearly during the OFDM symbol time. Subsequently, the two estimations of the symbol timing offset parameter are smoothed in order to obtain a fine tuned approximation of the Doppler scale. Additionally, the effects of weighting coefficients on smoothing the Doppler scale and on the performance of the receiver are also investigated. The proposed receiver is investigated, incorporating an improvement that includes fine tuning of the coarse timing synchronization in order to accommodate the time-varying Doppler. Based on this fine-tuned timing synchronization, an extension to the improved receiver is presented to assess the performance of two point correlations. The proposed algorithms' performances were investigated using real data obtained from an experiment that took place in the North Sea in 2009.
Energy Technology Data Exchange (ETDEWEB)
Pagowski, M O; Grell, G A; Devenyi, D; Peckham, S E; McKeen, S A; Gong, W; Monache, L D; McHenry, J N; McQueen, J; Lee, P
2006-02-02
Forecasts from seven air quality models and surface ozone data collected over the eastern USA and southern Canada during July and August 2004 provide a unique opportunity to assess benefits of ensemble-based ozone forecasting and devise methods to improve ozone forecasts. In this investigation, past forecasts from the ensemble of models and hourly surface ozone measurements at over 350 sites are used to issue deterministic 24-h forecasts using a method based on dynamic linear regression. Forecasts of hourly ozone concentrations as well as maximum daily 8-h and 1-h averaged concentrations are considered. It is shown that the forecasts issued with the application of this method have reduced bias and root mean square error and better overall performance scores than any of the ensemble members and the ensemble average. Performance of the method is similar to another method based on linear regression described previously by Pagowski et al., but unlike the latter, the current method does not require measurements from multiple monitors since it operates on individual time series. Improvement in the forecasts can be easily implemented and requires minimal computational cost.
Directory of Open Access Journals (Sweden)
Weihua Jin
2013-01-01
Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.
Comparison of the Noise Robustness of FVC Retrieval Algorithms Based on Linear Mixture Models
Directory of Open Access Journals (Sweden)
Hiroki Yoshioka
2011-07-01
Full Text Available The fraction of vegetation cover (FVC is often estimated by unmixing a linear mixture model (LMM to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results that can vary to a certain degree, depending on the model assumptions. For example, the robustness of the results depends on the presence of errors in the measured reflectance spectra. The objective of this study was to derive a factor that could be used to assess the robustness of LMM-based algorithms under a two-endmember assumption. The factor was derived from the analytical relationship between FVC values determined according to several previously described algorithms. The factor depended on the target spectra, endmember spectra, and choice of the spectral vegetation index. Numerical simulations were conducted to demonstrate the dependence and usefulness of the technique in terms of robustness against the measurement noise.
Energy Technology Data Exchange (ETDEWEB)
Hand, M. M.
1999-07-30
Variable-speed, horizontal axis wind turbines use blade-pitch control to meet specified objectives for three regions of operation. This paper focuses on controller design for the constant power production regime. A simple, rigid, non-linear turbine model was used to systematically perform trade-off studies between two performance metrics. Minimization of both the deviation of the rotor speed from the desired speed and the motion of the actuator is desired. The robust nature of the proportional-integral-derivative (PID) controller is illustrated, and optimal operating conditions are determined. Because numerous simulation runs may be completed in a short time, the relationship of the two opposing metrics is easily visualized. Traditional controller design generally consists of linearizing a model about an operating point. This step was taken for two different operating points, and the systematic design approach was used. A comparison of the optimal regions selected using the n on-linear model and the two linear models shows similarities. The linearization point selection does, however, affect the turbine performance slightly. Exploitation of the simplicity of the model allows surfaces consisting of operation under a wide range of gain values to be created. This methodology provides a means of visually observing turbine performance based upon the two metrics chosen for this study. Design of a PID controller is simplified, and it is possible to ascertain the best possible combination of controller parameters. The wide, flat surfaces indicate that a PID controller is very robust in this variable-speed wind turbine application.
Fischer, P.; Jardani, A.; Lecoq, N.
2017-03-01
Inverse problem permits to map the subsurface properties from a few observed data. The inverse problem can be physically constrained by a priori information on the property distribution in order to limit the nonuniqueness of the solution. The geostatistical information is often chosen as a priori information; however, when the field properties present a spatial locally distributed high variability, the geostatistical approach becomes inefficient. Therefore, we propose a new method adapted for fields presenting linear structures (such as a fractured field). The Cellular Automata-based Deterministic Inversion (CADI) method is, as far as we know when this paper is produced, the first inversion method which permits a deterministic inversion based on a Bayesian approach and using a dynamic optimization to generate different linear structures iteratively. The model is partitioned in cellular automaton subspaces, each one controlling a different zone of the model. A cellular automata subspace structures the properties of the model in two units ("structure" and "background") and control their dispensing direction and their values. The partitioning of the model in subspaces permits to monitor a large-scale structural model with only a few pilot-parameters and to generate linear structures with local direction changes. Thereby, the algorithm can easily handle with large-scale structures, and a sensitivity analysis is possible on these structural pilot-parameters, which permits to considerably accelerate the optimization process in order to find the best structural geometry. The algorithm has been successfully tested on simple, to more complex, theoretical models with different inversion techniques by using seismic and hydraulic data.
Energy Technology Data Exchange (ETDEWEB)
Hauptman, Jason S., E-mail: jhauptman@mednet.ucla.edu [Division of Stereotactic and Functional Neurosurgery, Department of Neurosurgery, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA (United States); Barkhoudarian, Garni; Safaee, Michael; Gorgulho, Alessandra [Division of Stereotactic and Functional Neurosurgery, Department of Neurosurgery, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA (United States); Tenn, Steven; Agazaryan, Nzhde; Selch, Michael [Department of Radiation Oncology, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA (United States); De Salles, Antonio A.F. [Division of Stereotactic and Functional Neurosurgery, Department of Neurosurgery, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA (United States); Department of Radiation Oncology, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA (United States)
2012-06-01
Purpose: Intracranial chordomas and chondrosarcomas are histologically low-grade, locally invasive tumors that infiltrate the skull base. Currently, consensus therapy includes surgical resection and adjuvant radiotherapy. Radiation delivery is typically limited by the proximity of these tumors to critical skull base structures. Methods: This is a retrospective review of 13 cases of chordomas and 2 cases of chondroid chondrosarcomas of the skull based treated with linear accelerator stereotactic radiotherapy (SRT, n = 10) or stereotactic radiosurgery (SRS, n = 5). The average time to the most recent follow-up visit was 4.5 years. The tumor characteristics, treatment details, and outcomes were recorded. Each radiation plan was reviewed, and the dosage received by the brainstem, optic apparatus, and pituitary was calculated. Results: Of the 10 patients treated with SRT, 6 were found to have unchanged or decreased tumor size as determined from radiographic follow-up. Of the 5 patients treated with SRS, 3 were found to have stable or unchanged tumors at follow-up. The complications included 1 SRT patient who developed endocrinopathy, 2 patients (1 treated with SRS and the other with SRT), who developed cranial neuropathy, and 1 SRS patient who developed visual deficits. Additionally, 1 patient who received both SRS and SRT within 2 years for recurrence experienced transient medial temporal lobe radiation changes that resolved. Conclusions: Where proton beam therapy is unavailable, linear accelerator-based SRT or radiosurgery remains a safe option for adjuvant therapy of chordomas and chondrosarcomas of the skull base. The exposure of the optic apparatus, pituitary stalk, and brainstem must be considered during planning to minimize complications. If the optic apparatus is included in the 80% isodose line, it might be best to fractionate therapy. Exposure of the pituitary stalk should be kept to <30 Gy to minimize endocrine dysfunction. Brainstem exposure should be
SPATIAL ANALYSIS BASED HEALTH AND SAFETY RISK ASSESSMENT FOR LINEAR CONSTRUCTION PROJECTS
Directory of Open Access Journals (Sweden)
H. Atay
2012-07-01
Full Text Available This paper describes an on-going study that aims to develop a web-based spatial decision support system model for proactive health and safety management in linear construction projects. Currently, health and safety management is usually performed reactively instead of proactive management since hazard identification and risk assessment is mostly performed on paper based documents that are not effectively used at site. This leads to accidents and fatalities at construction sites. The proposed system automatically identifies the spatial risks according to the topographic and layout map of the site, project specification and health and safety regulations by means of spatial analysis. It enables the workers and management personnel to access the possible hazards and thematic risk map of any portion of the construction site for linear projects. Finally, the described approach provides the proposed mitigation measures for the identified hazards. The developed system is expected to raise awareness in H&S among workers and engineers, and increase participation of workers to health and safety management.
Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong
2011-01-21
Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Lina V. Petrenko
2016-12-01
Full Text Available The purpose of research was the development of new and effective technique of electroplatings phase composition analysis by inversion voltammetric methods. As a result the possibility of the phase composition of the plated zinc-based alloys identification using anodic linear voltammetry in alkaline solutions was shown. The phase composition Zn–(0.27–9.4% Fe alloy electroplated from alkaline zincate solutions was defined based on voltammetry data. As part of the Zn–Fe alloys the phase of hexagonal structure was found which is absent in the equilibrium phase diagram. The ratio of hexagonal crystal lattice axes (c/a and the electron concentration (e/a for this phase are significantly different from the corresponding values for the primary solid solution η. From the analysis of c/a and e/a values of investigated Zn–Fe alloy the defined phase was identified as a solid solution phase type ε. It also was shown that anodic linear voltammetry accomplished in alkaline solutions is more sensitive to the identification of the phase composition of zinc alloys than the traditional X-ray method and stripping voltammetry.
Fernández-Fernández, Mario; Rodríguez-González, Pablo; García Alonso, J Ignacio
2016-10-01
We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two 13 C atoms ( 13 C 2 -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of 13 C 2 -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% 13 C 2 -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Xie, Shengkun; Krishnan, Sridhar
2013-02-01
In epilepsy diagnosis or epileptic seizure detection, much effort has been focused on finding effective combination of feature extraction and classification methods. In this paper, we develop a wavelet-based sparse functional linear model for representation of EEG signals. The aim of this modeling approach is to capture discriminative random components of EEG signals using wavelet variances. To achieve this goal, a forward search algorithm is proposed for determination of an appropriate wavelet decomposition level. Two EEG databases from University of Bonn and University of Freiburg are used for illustration of applicability of the proposed method to both epilepsy diagnosis and epileptic seizure detection problems. For this data considered, we show that wavelet-based sparse functional linear model with a simple classifier such as 1-NN classification method leads to higher classification results than those obtained using other complicated methods such as support vector machine. This approach produces a 100% classification accuracy for various classification tasks using the EEG database from University of Bonn, and outperforms many other state-of-the-art techniques. The proposed classification scheme leads to 99% overall classification accuracy for the EEG data from University of Freiburg.
Complexity-reduced implementations of complete and null-space-based linear discriminant analysis.
Lu, Gui-Fu; Zheng, Wenming
2013-10-01
Dimensionality reduction has become an important data preprocessing step in a lot of applications. Linear discriminant analysis (LDA) is one of the most well-known dimensionality reduction methods. However, the classical LDA cannot be used directly in the small sample size (SSS) problem where the within-class scatter matrix is singular. In the past, many generalized LDA methods has been reported to address the SSS problem. Among these methods, complete linear discriminant analysis (CLDA) and null-space-based LDA (NLDA) provide good performances. The existing implementations of CLDA are computationally expensive. In this paper, we propose a new and fast implementation of CLDA. Our proposed implementation of CLDA, which is the most efficient one, is equivalent to the existing implementations of CLDA in theory. Since CLDA is an extension of null-space-based LDA (NLDA), our implementation of CLDA also provides a fast implementation of NLDA. Experiments on some real-world data sets demonstrate the effectiveness of our proposed new CLDA and NLDA algorithms. Copyright © 2013 Elsevier Ltd. All rights reserved.
Non linear dynamics of memristor based 3rd order oscillatory system
Talukdar, Abdul Hafiz Ibne
2012-07-23
In this paper, we report for the first time the nonlinear dynamics of three memristor based phase shift oscillators, and consider them as a plausible solution for the realization of parametric oscillation as an autonomous linear time variant system. Sustained oscillation is reported through oscillating resistance while time dependent poles are present. The memristor based phase shift oscillator is explored further by varying the parameters so as to present the resistance of the memristor as a time varying parameter, thus potentially eliminating the need of external periodic forces in order for it to oscillate. Multi memristors, used simultaneously with similar and different parameters, are investigated in this paper. Mathematical formulas for analyzing such oscillators are verified with simulation results and are found to be in good agreement. © 2011 Elsevier Ltd. All rights reserved.
Ultrafast all-optical clock recovery based on phase-only linear optical filtering
DEFF Research Database (Denmark)
Maram, Reza; Kong, Deming; Galili, Michael
2014-01-01
We report on a novel, efficient technique for all-optical clock recovery from RZ-OOK data signals based on spectral phase-only (all-pass) optical filtering. This technique significantly enhances both the recovered optical clock quality and energy efficiency in comparison with conventional amplitu...... optical filtering approaches using a Fabry-Perot filter. The proposed concept is validated through recovery of the optical clock from a 640 Gbit/s RZ-OOK data signal using a commercial linear optical waveshaper. (C) 2014 Optical Society of America......We report on a novel, efficient technique for all-optical clock recovery from RZ-OOK data signals based on spectral phase-only (all-pass) optical filtering. This technique significantly enhances both the recovered optical clock quality and energy efficiency in comparison with conventional amplitude...
hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.
Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Zhou, Manli; Zhou, Fengfeng
2017-01-01
Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variety of functions and a patient with multiple diseases. The majority of existing classification algorithms assumes each sample with only one class label, and the multi-label classification problem remains to be a challenge for biomedical researchers. This study proposes a novel multi-label learning algorithm, hMuLab, by integrating both feature-based and neighbor-based similarity scores. The multiple linear regression modeling techniques make hMuLab capable of producing multiple label assignments for a query sample. The comparison results over six commonly-used multi-label performance measurements suggest that hMuLab performs accurately and stably for the biomedical datasets, and may serve as a complement to the existing literature.
Han, Xuemei; Peng, Hu; Cai, Bo
2009-08-01
The high frame rate (HFR) ultrasonic imaging system based on linear frequency-modulated (LFM) signal constructs images at a high frame rate; the signal-to-noise ratio (SNR) of this system can also be improved. Unfortunately, such pulse compression methods that increase the SNR usually cause range sidelobe artifacts. In an imaging situation, the effects of the sidelobes extending on either side of the compressed pulse will be self-noise along the axial direction and masking of weaker echoes. The improvement on high frame rate ultrasonic imaging system based on LFM signal is considered in this paper. In this proposed scheme, a predistorted LFM signal is used as excited signal and a mismatched filter is applied on receiving end. The results show that the proposed HFR ultrasonic imaging system can achieve higher SNR and the axial resolution is also improved.
A Versatile Multiple Target Detection System Based on DNA Nano-assembled Linear FRET Arrays.
Li, Yansheng; Du, Hongwu; Wang, Wenqian; Zhang, Peixun; Xu, Liping; Wen, Yongqiang; Zhang, Xueji
2016-05-27
DNA molecules have been utilized both as powerful synthetic building blocks to create nanoscale architectures and as inconstant programmable templates for assembly of biosensors. In this paper, a versatile, scalable and multiplex detection system is reported based on an extending fluorescent resonance energy transfer (FRET) cascades on a linear DNA assemblies. Seven combinations of three kinds of targets are successfully detected through the changes of fluorescence spectra because of the three-steps FRET or non-FRET continuity mechanisms. This nano-assembled FRET-based nanowire is extremely significant for the development of rapid, simple and sensitive detection system. The method used here could be extended to a general platform for multiplex detection through more-step FRET process.
Control allocation of ASV based on linear programming and fuzzy logic
Chi, Pei; Chen, Zongji; Zhou, Rui
2006-11-01
Future Aero Space Vehicle flies through both the atmospheric and extra atmospheric fields, which implies the autonomy and adaptability to the uncertainties from the system faults and changing environments. Algorithms based on fuzzy logic and linear programming are presented, which can implement the autonomous control reconfigurations under uncertainties via the redundant actuators. The compensation branch minimizes the difference between the desired control objectives and the actual achievable control if the control power is deficient. Otherwise the optimization branch optimizes some sub-objectives by utilizing the excess control power. The fuzzy logic-based regulator tunes the weight vector of the objective functions by the expert rules to obtain the optimized allocation results under various environments with considerations of the control effectiveness. It is illustrated that the algorithms can satisfy the control performance, save the fuel and smooth the allocation output.
Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods
Perumal, Muthiah; Tayfur, Gokmen; Rao, C. Madhusudana; Gurarslan, Gurhan
2017-03-01
Two variants of the Muskingum flood routing method formulated for accounting nonlinearity of the channel routing process are investigated in this study. These variant methods are: (1) The three-parameter conceptual Nonlinear Muskingum (NLM) method advocated by Gillin 1978, and (2) The Variable Parameter McCarthy-Muskingum (VPMM) method recently proposed by Perumal and Price in 2013. The VPMM method does not require rigorous calibration and validation procedures as required in the case of NLM method due to established relationships of its parameters with flow and channel characteristics based on hydrodynamic principles. The parameters of the conceptual nonlinear storage equation used in the NLM method were calibrated using the Artificial Intelligence Application (AIA) techniques, such as the Genetic Algorithm (GA), the Differential Evolution (DE), the Particle Swarm Optimization (PSO) and the Harmony Search (HS). The calibration was carried out on a given set of hypothetical flood events obtained by routing a given inflow hydrograph in a set of 40 km length prismatic channel reaches using the Saint-Venant (SV) equations. The validation of the calibrated NLM method was investigated using a different set of hypothetical flood hydrographs obtained in the same set of channel reaches used for calibration studies. Both the sets of solutions obtained in the calibration and validation cases using the NLM method were compared with the corresponding solutions of the VPMM method based on some pertinent evaluation measures. The results of the study reveal that the physically based VPMM method is capable of accounting for nonlinear characteristics of flood wave movement better than the conceptually based NLM method which requires the use of tedious calibration and validation procedures.
Gain Scheduling Control of Nonlinear Shock Motion Based on Equilibrium Manifold Linearization Model
National Research Council Canada - National Science Library
Cui Tao Yu Daren Bao Wen Yang Yongbin
2007-01-01
The equilibrium manifold linearization model of nonlinear shock motion is of higher accuracy and lower complexity over other models such as the small perturbation model and the piecewise-linear model...
Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.
Wu, Panpan; Xia, Kewen; Yu, Hengyong
2016-11-01
Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
3-D ultrasonic strain imaging based on a linear scanning system.
Huang, Qinghua; Xie, Bo; Ye, Pengfei; Chen, Zhaohong
2015-02-01
This paper introduces a 3-D strain imaging method based on a freehand linear scanning mode. We designed a linear sliding track with a position sensor and a height-adjustable holder to constrain the movement of an ultrasound probe in a freehand manner. When moving the probe along the sliding track, the corresponding positional measures for the probe are transmitted via a wireless communication module based on Bluetooth in real time. In a single examination, the probe is scanned in two sweeps in which the height of the probe is adjusted by the holder to collect the pre- and postcompression radio-frequency echoes, respectively. To generate a 3-D strain image, a volume cubic in which the voxels denote relative strains for tissues is defined according to the range of the two sweeps. With respect to the post-compression frames, several slices in the volume are determined and the pre-compression frames are re-sampled to precisely correspond to the post-compression frames. Thereby, a strain estimation method based on minimizing a cost function using dynamic programming is used to obtain the 2-D strain image for each pair of frames from the re-sampled pre-compression sweep and the post-compression sweep, respectively. A software system is developed for volume reconstruction, visualization, and measurement of the 3-D strain images. The experimental results show that high-quality 3-D strain images of phantom and human tissues can be generated by the proposed method, indicating that the proposed system can be applied for real clinical applications (e.g., musculoskeletal assessments).
Development of photoelectric balanced car based on the linear CCD sensor
Directory of Open Access Journals (Sweden)
Wang Feng
2016-01-01
Full Text Available The smart car is designed based on Freescale’s MC9S12XS128 and a linear CCD camera. The linear CCD collects the road information and sends it to MCU through the operational amplifier. The PID control algorithm, the proportional–integral–derivative control algorithm, is adopted synthetically to control the smart car. First, the smart car’s inclination and angular velocity are detect through the accelerometers and gyro sensors, then the PD control algorithm, the proportional–derivative control algorithm, is employed to make the smart car have the ability of two-wheeled self-balancing. Second, the speed of wheel obtained by the encoder is fed back to the MCU by way of pulse signal, then the PI control algorithm, the proportional–integral control algorithm, is employed to make the speed of smart car reach the set point in the shortest possible time and stabilize at the set point. Finally, the PD control algorithm is used to regulate the smart car’s turning angle to make the smart car respond quickly while the smart car is passing the curve path. The smart car can realize the self-balancing control of two wheels and track automatically the black and while lines to march.
Locally linear representation Fisher criterion based tumor gene expressive data classification.
Li, Bo; Tian, Bei-Bei; Zhang, Xiao-Long; Zhang, Xiao-Ping
2014-10-01
Tumor gene expressive data are characterized by a large amount of genes with only a small amount of observations, which always appear with high dimensionality. So it is necessary to reduce the dimensionality before identifying their genre. In this paper, a discriminant manifold learning method, named locally linear representation Fisher criterion (LLRFC), is applied to extract features from tumor gene expressive data. In LLRFC, an inter-class graph and an intra-class graph are constructed based on their genre information, where any tumor gene expressive data in the inter-class graph should select k nearest neighbors with different class labels and in the intra-class graph the k nearest neighbors for any tumor gene expressive data must be sampled from those with the same class. And then the locally least linear reconstruction is introduced to optimize the corresponding weights in both graphs. Moreover, a Fisher criterion is modeled to explore a low dimensional subspace where the reconstruction errors in the inter-class graph can be maximized and the reconstruction errors in the intra-class graph can be minimized, simultaneously. Experiments on some benchmark tumor gene expressive data have been conducted with some related algorithms, by which the proposed LLRFC has been validated to be efficient. Copyright © 2014 Elsevier Ltd. All rights reserved.
Dynamic interference fringe processing algorithms based on non-linear optimization
Ermolaev, Petr A.; Volynsky, Maxim A.; Tomarzhevskaya, Anna S.
2017-04-01
The paper deals with an approach to dynamic parameters estimation of interferometric signals based on non-linear optimization technique. The features of the approach are demonstrated on the example of the gradient descent method as simple iterative non-linear optimization algorithm. The possibilities of using this approach to refine the signal parameters estimates obtained by the extended Kalman filter are considered. The model of one-dimensional interferometric signal is presented. The results of simulated signals processing are analyzed. It was investigated how the quantity of gradient descent iterations influences the quality of parameters estimation. It is shown that the gradient descent provides 65% increase of signal-to-noise ratio for reconstructed signal in comparison with original signal. The proposed method in combination with the extended Kalman filter allows to decrease the amplitude estimation error compared to the unmodified extended Kalman filter. The processing time evaluation results are presented. The recommendations on using proposed approach for interferometric data processing are given.
EEG-based BCI for the linear control of an upper-limb neuroprosthesis.
Vidaurre, Carmen; Klauer, Christian; Schauer, Thomas; Ramos-Murguialday, Ander; Müller, Klaus-Robert
2016-11-01
Assistive technologies help patients to reacquire interacting capabilities with the environment and improve their quality of life. In this manuscript we present a feasibility study in which healthy users were able to use a non-invasive Motor Imagery (MI)-based brain computer interface (BCI) to achieve linear control of an upper-limb functional electrical stimulation (FES) controlled neuro-prosthesis. The linear control allowed the real-time computation of a continuous control signal that was used by the FES system to physically set the stimulation parameters to control the upper-limb position. Even if the nature of the task makes the operation very challenging, the participants achieved a mean selection accuracy of 82.5% in a target selection experiment. An analysis of limb kinematics as well as the positioning precision was performed, showing the viability of using a BCI-FES system to control upper-limb reaching movements. The results of this study constitute an accurate use of an online non-invasive BCI to operate a FES-neuroprosthesis setting a step toward the recovery of the control of an impaired limb with the sole use of brain activity. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.
Canepa, Edward S.
2013-01-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.
Canepa, Edward S.
2013-09-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.
Reoptimization of Intensity Modulated Proton Therapy Plans Based on Linear Energy Transfer
Energy Technology Data Exchange (ETDEWEB)
Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Botas, Pablo [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Faculty of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg (Germany); Giantsoudi, Drosoula; Gorissen, Bram L.; Paganetti, Harald [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)
2016-12-01
Purpose: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution. Methods and Materials: To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET. Results: The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.
Region-Based Association Test for Familial Data under Functional Linear Models.
Directory of Open Access Journals (Sweden)
Gulnara R Svishcheva
Full Text Available Region-based association analysis is a more powerful tool for gene mapping than testing of individual genetic variants, particularly for rare genetic variants. The most powerful methods for regional mapping are based on the functional data analysis approach, which assumes that the regional genome of an individual may be considered as a continuous stochastic function that contains information about both linkage and linkage disequilibrium. Here, we extend this powerful approach, earlier applied only to independent samples, to the samples of related individuals. To this end, we additionally include a random polygene effects in functional linear model used for testing association between quantitative traits and multiple genetic variants in the region. We compare the statistical power of different methods using Genetic Analysis Workshop 17 mini-exome family data and a wide range of simulation scenarios. Our method increases the power of regional association analysis of quantitative traits compared with burden-based and kernel-based methods for the majority of the scenarios. In addition, we estimate the statistical power of our method using regions with small number of genetic variants, and show that our method retains its advantage over burden-based and kernel-based methods in this case as well. The new method is implemented as the R-function 'famFLM' using two types of basis functions: the B-spline and Fourier bases. We compare the properties of the new method using models that differ from each other in the type of their function basis. The models based on the Fourier basis functions have an advantage in terms of speed and power over the models that use the B-spline basis functions and those that combine B-spline and Fourier basis functions. The 'famFLM' function is distributed under GPLv3 license and is freely available at http://mga.bionet.nsc.ru/soft/famFLM/.
A Non-Linear Upscaling Approach for Wind Turbines Blades Based on Stresses
Castillo Capponi, P.; Van Bussel, G.J.W.; Ashuri, T.; Kallesoe, B.
2011-01-01
The linear scaling laws for upscaling wind turbine blades show a linear increase of stresses due to the weight. However, the stresses should remain the same for a suitable design. Application of linear scaling laws may lead to an upscaled blade that may not be any more a feasible design. In this
National Research Council Canada - National Science Library
Thawley, David
2003-01-01
.... When historical data exists on evaluation measures and performance of alternatives, linear programming and genetic algorithm based optimization may be used to derive historically optimal weights for a hierarchy...
National Research Council Canada - National Science Library
Ipekci, Arif
2002-01-01
...) to explore non-linearity and intangibles inherent in guerrilla warfare. An infiltration scenario is developed based on the author's experiences fighting guerrillas in the mountains of Southeast Turkey...
Characterization of a measurement-based noiseless linear amplifier and its applications
Zhao, Jie; Haw, Jing Yan; Symul, Thomas; Lam, Ping Koy; Assad, Syed M.
2017-07-01
A noiseless linear amplifier (NLA) adds no noise to the signals it processes, which works only in a probabilistic way. It can be realized approximately with either a physical implementation that truncates the working space of the NLA on a photon-number basis or a measurement-based implementation that realizes the truncation virtually by a bounded postselection filter. To examine the relationship between these two approximate NLAs, we characterize in detail the measurement-based NLA and compare it with its physical counterpart in terms of their abilities to preserve the state Gaussianity and their probability of success. The link between these amplifiers is further clarified by integrating them into a measure-and-prepare setup. We stress the equivalence between the physical and the measurement-based approaches holds only when the effective parameters, the amplification gain, the cutoff, and the amplitude of the input state, are taken into account. Finally, we construct a 1-to-infinity cloner using the two amplifiers and show that a fidelity surpassing the no-cloning limit is achievable with the measurement-based NLA.
Approach for Self-Calibrating CO2 Measurements with Linear Membrane-Based Gas Sensors
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Detlef Lazik
2016-11-01
Full Text Available Linear membrane-based gas sensors that can be advantageously applied for the measurement of a single gas component in large heterogeneous systems, e.g., for representative determination of CO2 in the subsurface, can be designed depending on the properties of the observation object. A resulting disadvantage is that the permeation-based sensor response depends on operating conditions, the individual site-adapted sensor geometry, the membrane material, and the target gas component. Therefore, calibration is needed, especially of the slope, which could change over several orders of magnitude. A calibration-free approach based on an internal gas standard is developed to overcome the multi-criterial slope dependency. This results in a normalization of sensor response and enables the sensor to assess the significance of measurement. The approach was proofed on the example of CO2 analysis in dry air with tubular PDMS membranes for various CO2 concentrations of an internal standard. Negligible temperature dependency was found within an 18 K range. The transformation behavior of the measurement signal and the influence of concentration variations of the internal standard on the measurement signal were shown. Offsets that were adjusted based on the stated theory for the given measurement conditions and material data from the literature were in agreement with the experimentally determined offsets. A measurement comparison with an NDIR reference sensor shows an unexpectedly low bias (<1% of the non-calibrated sensor response, and comparable statistical uncertainty.
Approach for Self-Calibrating CO2 Measurements with Linear Membrane-Based Gas Sensors
Lazik, Detlef; Sood, Pramit
2016-01-01
Linear membrane-based gas sensors that can be advantageously applied for the measurement of a single gas component in large heterogeneous systems, e.g., for representative determination of CO2 in the subsurface, can be designed depending on the properties of the observation object. A resulting disadvantage is that the permeation-based sensor response depends on operating conditions, the individual site-adapted sensor geometry, the membrane material, and the target gas component. Therefore, calibration is needed, especially of the slope, which could change over several orders of magnitude. A calibration-free approach based on an internal gas standard is developed to overcome the multi-criterial slope dependency. This results in a normalization of sensor response and enables the sensor to assess the significance of measurement. The approach was proofed on the example of CO2 analysis in dry air with tubular PDMS membranes for various CO2 concentrations of an internal standard. Negligible temperature dependency was found within an 18 K range. The transformation behavior of the measurement signal and the influence of concentration variations of the internal standard on the measurement signal were shown. Offsets that were adjusted based on the stated theory for the given measurement conditions and material data from the literature were in agreement with the experimentally determined offsets. A measurement comparison with an NDIR reference sensor shows an unexpectedly low bias (sensor response, and comparable statistical uncertainty. PMID:27869656
Discovering short linear protein motif based on selective training of profile hidden Markov models.
Song, Tao; Gu, Hong
2015-07-21
Short linear motifs (SLiMs) in proteins are relatively conservative sequence patterns within disordered regions of proteins, typically 3-10 amino acids in length. They play an important role in mediating protein-protein interactions. Discovering SLiMs by computational methods has attracted more and more attention, most of which were based on regular expressions and profiles. In this paper, a de novo motif discovery method was proposed based on profile hidden Markov models (HMMs), which can not only provide the emission probabilities of amino acids in the defined positions of SLiMs, but also model the undefined positions. We adopted the ordered region masking and the relative local conservation (RLC) masking to improve the signal to noise ratio of the query sequences while applying evolutionary weighting to make the important sequences in evolutionary process get more attention by the selective training of profile HMMs. The experimental results show that our method and the profile-based method returned different subsets within a SLiMs dataset, and the performance of the two approaches are equivalent on a more realistic discovery dataset. Profile HMM-based motif discovery methods complement the existing methods and provide another way for SLiMs analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation
Directory of Open Access Journals (Sweden)
Chunqing Li
2012-01-01
Full Text Available The computer simulation of the membrane bioreactor MBR has become the research focus of the MBR simulation. In order to compensate for the defects, for example, long test period, high cost, invisible equipment seal, and so forth, on the basis of conducting in-depth study of the mathematical model of the MBR, combining with neural network theory, this paper proposed a three-dimensional simulation system for MBR wastewater treatment, with fast speed, high efficiency, and good visualization. The system is researched and developed with the hybrid programming of VC++ programming language and OpenGL, with a multifactor linear regression model of affecting MBR membrane fluxes based on neural network, applying modeling method of integer instead of float and quad tree recursion. The experiments show that the three-dimensional simulation system, using the above models and methods, has the inspiration and reference for the future research and application of the MBR simulation technology.
Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling
DEFF Research Database (Denmark)
Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm
2014-01-01
In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate...... of the shift operator associated with the particular prediction problem considered. The second method uses the alternative Cauchy bound to impose a convex constraint on the predictor in the 1-norm error minimization. These methods are compared with two existing methods: the Burg method, based on the 1-norm...... minimization of the forward and backward prediction error, and the iteratively reweighted 2-norm minimization known to converge to the 1-norm minimization with an appropriate selection of weights. The evaluation gives proof of the effectiveness of the new methods, performing as well as unconstrained 1-norm...
Directory of Open Access Journals (Sweden)
Yizhou Yang
2017-01-01
Full Text Available To diagnose mechanical faults of rotor-bearing-casing system by analyzing its casing vibration signal, this paper proposes a training procedure of a fault classifier based on variational mode decomposition (VMD, local linear embedding (LLE, and support vector machine (SVM. VMD is used first to decompose the casing signal into several modes, which are subsignals usually modulated by fault frequencies. Vibrational features are extracted from both VMD subsignals and the original one. LLE is employed here to reduce the dimensionality of these extracted features and make the samples more separable. Then low-dimensional data sets are used to train the multiclass SVM whose accuracy is tested by classifying the test samples. When the parameters of LLE and SVM are well optimized, this proposed method performs well on experimental data, showing its capacity of diagnosing casing vibration faults.
Linear programming to build food-based dietary guidelines: Romanian food baskets
DEFF Research Database (Denmark)
Parlesak, Alexandr; Robertson, Aileen; Hondru, Gabriela
As in many Member States of the WHO European Region, Romania is seeing an increase in the prevalence of overweight and obesity, particularly among children and adolescents. This is a major risk factor for the development of noncommunicable diseases (NCDs), and innovative approaches using a (“heal......As in many Member States of the WHO European Region, Romania is seeing an increase in the prevalence of overweight and obesity, particularly among children and adolescents. This is a major risk factor for the development of noncommunicable diseases (NCDs), and innovative approaches using......, potatoes and fish and considerably less meat, fats, oils and sugar. In conclusion, the linear programming methodology can facilitate the development of national dietary recommendations that meet both recommended nutrient intake values and WHO food-based dietary guidelines in a cost-efficient manner. How...
Joint polarization tracking and channel equalization based on radius-directed linear Kalman filter
Zhang, Qun; Yang, Yanfu; Zhong, Kangping; Liu, Jie; Wu, Xiong; Yao, Yong
2018-01-01
We propose a joint polarization tracking and channel equalization scheme based on radius-directed linear Kalman filter (RD-LKF) by introducing the butterfly finite-impulse-response (FIR) filter in our previously proposed RD-LKF method. Along with the fast polarization tracking, it can also simultaneously compensate the inter-symbol interference (ISI) effects including residual chromatic dispersion and polarization mode dispersion. Compared with the conventional radius-directed equalizer (RDE) algorithm, it is demonstrated experimentally that three times faster convergence speed, one order of magnitude better tracking capability, and better BER performance is obtained in polarization division multiplexing 16 quadrature amplitude modulation system. Besides, the influences of the algorithm parameters on the convergence and the tracking performance are investigated by numerical simulation.
Directory of Open Access Journals (Sweden)
Velislava Spasova
2016-06-01
Full Text Available The paper presents a novel fast, real-time and privacy protecting algorithm for fall detection based on geometric properties of the human silhouette and a linear support vector machine. The algorithm uses infrared and visible light imagery in order to detect the human. A simple real-time human silhouette extraction algorithm has been developed and used to extract features for training of the support vector machine. The achieved sensitivity and specificity of the proposed approach are over 97% which match state of the art research in the area of fall detection. The developed solution uses low-cost hardware components and open source software library and is suitable for usage in assistive systems for the home or nursing homes.
Differential-Drive Mobile Robot Control Design based-on Linear Feedback Control Law
Nurmaini, Siti; Dewi, Kemala; Tutuko, Bambang
2017-04-01
This paper deals with the problem of how to control differential driven mobile robot with simple control law. When mobile robot moves from one position to another to achieve a position destination, it always produce some errors. Therefore, a mobile robot requires a certain control law to drive the robot’s movement to the position destination with a smallest possible error. In this paper, in order to reduce position error, a linear feedback control is proposed with pole placement approach to regulate the polynoms desired. The presented work leads to an improved understanding of differential-drive mobile robot (DDMR)-based kinematics equation, which will assist to design of suitable controllers for DDMR movement. The result show by using the linier feedback control method with pole placement approach the position error is reduced and fast convergence is achieved.
Qureshi, Farah; Khuhawar, Muhammad Yar; Jahangir, Taj Muhammad; Channar, Abdul Hamid
2016-01-01
Five new linear Schiff base polymers having azomethine structures, ether linkages and extended aliphatic chain lengths with flexible spacers were synthesized by polycondensation of dialdehyde (monomer) with aliphatic and aromatic diamines. The formation yields of monomer and polymers were obtained within 75-92%. The polymers with flexible spacers of n-hexane were somewhat soluble in acetone, chloroform, THF, DMF and DMSO on heating. The monomer and polymers were characterized by melting point, elemental microanalysis, FT-IR, (1)HNMR, UV-Vis spectroscopy, thermogravimetry (TG), differential thermal analysis (DTA), fluorescence emission, scanning electron microscopy (SEM) and viscosities and thermodynamic parameters measurements of their dilute solutions. The studies supported formation of the monomer and polymers and on the basis of these studies their structures have been assigned. The synthesized polymers were tested for their antibacterial and antifungal activities.
Generalization of the ordinary state-based peridynamic model for isotropic linear viscoelasticity
Delorme, Rolland; Tabiai, Ilyass; Laberge Lebel, Louis; Lévesque, Martin
2017-02-01
This paper presents a generalization of the original ordinary state-based peridynamic model for isotropic linear viscoelasticity. The viscoelastic material response is represented using the thermodynamically acceptable Prony series approach. It can feature as many Prony terms as required and accounts for viscoelastic spherical and deviatoric components. The model was derived from an equivalence between peridynamic viscoelastic parameters and those appearing in classical continuum mechanics, by equating the free energy densities expressed in both frameworks. The model was simplified to a uni-dimensional expression and implemented to simulate a creep-recovery test. This implementation was finally validated by comparing peridynamic predictions to those predicted from classical continuum mechanics. An exact correspondence between peridynamics and the classical continuum approach was shown when the peridynamic horizon becomes small, meaning peridynamics tends toward classical continuum mechanics. This work provides a clear and direct means to researchers dealing with viscoelastic phenomena to tackle their problem within the peridynamic framework.
Directory of Open Access Journals (Sweden)
S. Maktoobi
2014-10-01
Full Text Available Switching is a principle process in digital computers and signal processing systems. The growth of optical signal processing systems, draws particular attention to design of ultra-fast optical switches. In this paper, All Optical Switches in linear state Based On photonic crystal Directional coupler is analyzed and simulated. Among different methods, the finite difference time domain method (FDTD is a preferable method and is used. We have studied the application of photonic crystal lattices, the physics of optical switching and photonic crystal Directional coupler. In this paper, Electric field intensity and the power output that are two factors to improve the switching performance and the device efficiency are investigated and simulated. All simulations are performed by COMSOL software.
Directory of Open Access Journals (Sweden)
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Rectified-Linear-Unit-Based Deep Learning for Biomedical Multi-label Data.
Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Cai, Yunpeng; Wang, Guoqing; Zhou, Fengfeng
2017-09-01
Disease diagnosis is one of the major data mining questions by the clinicians. The current diagnosis models usually have a strong assumption that one patient has only one disease, i.e. a single-label data mining problem. But the patients, especially when at the late stages, may have more than one disease and require a multi-label diagnosis. The multi-label data mining is much more difficult than a single-label one, and very few algorithms have been developed for this situation. Deep learning is a data mining algorithm with highly dense inner structure and has achieved many successful applications in the other areas. We propose a hypothesis that rectified-linear-unit-based deep learning algorithm may also be good at the clinical questions, by revising the last layer as a multi-label output. The proof-of-concept experimental data support the hypothesis, and the community may be interested in trying more applications.
Hu, Fang; Liu, Yuhua
2015-02-01
The evaluation of node importance has great significance to complex network, so it is important to seek and protect important nodes to ensure the security and stability of the entire network. At present, most evaluation algorithms of node importance adopt the single-index methods, which are incomplete and limited, and cannot fully reflect the complex situation of network. In this paper, after synthesizing multi-index factors of node importance, including eigenvector centrality, betweenness centrality, closeness centrality, degree centrality, mutual-information, etc., the authors are proposing a new multi-index evaluation algorithm of identifying important nodes in complex networks based on linear discriminant analysis (LDA). In order to verify the validity of this algorithm, a series of simulation experiments have been done. Through comprehensive analysis, the simulation results show that the new algorithm is more rational, effective, integral and accurate.
Filimonov, A. B.; Filimonov, N. B.
2017-07-01
The problem of dynamic decoupling of control channels for multidimensional objects is aimed at autonomization of control of output variables of the object, which is ensured by means of including special correcting links into the control system. A new method of solving this problem is proposed, where decoupling is provided by a block of dynamic correction. The desired result of decoupling is represented by a standard model with separate control channels. The mathematical apparatus applied for calculating the correction block is based on the formalism of linear-quadratic optimization, where the optimized integral quadratic criteria serve as a measure of deviation of the transient characteristics of the corrected object from their desired (standard) values.
Understanding MCP-MOD dose finding as a method based on linear regression.
Thomas, Neal
2017-11-30
MCP-MOD is a testing and model selection approach for clinical dose finding studies. During testing, contrasts of dose group means are derived from candidate dose response models. A multiple-comparison procedure is applied that controls the alpha level for the family of null hypotheses associated with the contrasts. Provided at least one contrast is significant, a corresponding set of "good" candidate models is identified. The model generating the most significant contrast is typically selected. There have been numerous publications on the method. It was endorsed by the European Medicines Agency. The MCP-MOD procedure can be alternatively represented as a method based on simple linear regression, where "simple" refers to the inclusion of an intercept and a single predictor variable, which is a transformation of dose. It is shown that the contrasts are equal to least squares linear regression slope estimates after a rescaling of the predictor variables. The test for each contrast is the usual t statistic for a null slope parameter, except that a variance estimate with fewer degrees of freedom is used in the standard error. Selecting the model corresponding to the most significant contrast P value is equivalent to selecting the predictor variable yielding the smallest residual sum of squares. This criteria orders the models like a common goodness-of-fit test, but it does not assure a good fit. Common inferential methods applied to the selected model are subject to distortions that are often present following data-based model selection. Copyright © 2017 John Wiley & Sons, Ltd.
Energy Technology Data Exchange (ETDEWEB)
AlAfeef, Ala, E-mail: a.al-afeef.1@research.gla.ac.uk [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); School of Computing Science, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Bobynko, Joanna [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Cockshott, W. Paul. [School of Computing Science, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Craven, Alan J. [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Zuazo, Ian; Barges, Patrick [ArcelorMittal Maizières Research, Maizières-lès-Metz 57283 (France); MacLaren, Ian, E-mail: ian.maclaren@glasgow.ac.uk [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom)
2016-11-15
We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionally, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS. - Highlights: • DualEELS is essential for chemically sensitive electron tomography using EELS. • A new compressed sensing based algorithm (DLET) gives high fidelity reconstruction. • This combination of DualEELS and DLET will give reliable results from few projections.
Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen
2012-06-01
To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.
Linearly constrained minimax optimization
DEFF Research Database (Denmark)
Madsen, Kaj; Schjær-Jacobsen, Hans
1978-01-01
We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...
MLR-tagging: informative SNP selection for unphased genotypes based on multiple linear regression.
He, Jingwu; Zelikovsky, Alexander
2006-10-15
The search for the association between complex diseases and single nucleotide polymorphisms (SNPs) or haplotypes has recently received great attention. For these studies, it is essential to use a small subset of informative SNPs accurately representing the rest of the SNPs. Informative SNP selection can achieve (1) considerable budget savings by genotyping only a limited number of SNPs and computationally inferring all other SNPs or (2) necessary reduction of the huge SNP sets (obtained, e.g. from Affymetrix) for further fine haplotype analysis. A novel informative SNP selection method for unphased genotype data based on multiple linear regression (MLR) is implemented in the software package MLR-tagging. This software can be used for informative SNP (tag) selection and genotype prediction. The stepwise tag selection algorithm (STSA) selects positions of the given number of informative SNPs based on a genotype sample population. The MLR SNP prediction algorithm predicts a complete genotype based on the values of its informative SNPs, their positions among all SNPs, and a sample of complete genotypes. An extensive experimental study on various datasets including 10 regions from HapMap shows that the MLR prediction combined with stepwise tag selection uses fewer tags than the state-of-the-art method of Halperin et al. (2005). MLR-Tagging software package is publicly available at http://alla.cs.gsu.edu/~software/tagging/tagging.html
Mechanical Analogy-based Iterative Method for Solving a System of Linear Equations
Directory of Open Access Journals (Sweden)
Yu. V. Berchun
2015-01-01
Full Text Available The paper reviews prerequisites to creating a variety of the iterative methods to solve a system of linear equations (SLE. It considers the splitting methods, variation-type methods, projection-type methods, and the methods of relaxation.A new iterative method based on mechanical analogy (the movement without resistance of a material point, that is connected by ideal elastically-linear constraints with unending guides defined by equations of solved SLE. The mechanical system has the unique position of stable equilibrium, the coordinates of which correspond to the solution of linear algebraic equation. The model of the mechanical system is a system of ordinary differential equations of the second order, integration of which allows you to define the point trajectory. In contrast to the classical methods of relaxation the proposed method does not ensure a trajectory passage through the equilibrium position. Thus the convergence of the method is achieved through the iterative stop of a material point at the moment it passes through the next (from the beginning of the given iteration minimum of potential energy. After that the next iteration (with changed initial coordinates starts.A resource-intensive process of numerical integration of differential equations in order to obtain a precise law of motion (at each iteration is replaced by defining its approximation. The coefficients of the approximating polynomial of the fourth order are calculated from the initial conditions, including higher-order derivatives. The resulting approximation enables you to evaluate the kinetic energy of a material point to calculate approximately the moment of time to reach the maximum kinetic energy (and minimum of the potential one, i.e. the end of the iteration.The software implementation is done. The problems with symmetric positive definite matrix, generated as a result of using finite element method, allowed us to examine a convergence rate of the proposed method
Selvaraj, Jerritta; Murugappan, Murugappan; Wan, Khairunizam; Yaacob, Sazali
2013-05-16
Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals. Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm. Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively. The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system.
On the non-linear dynamics of a space platform based mobile flexible manipulator
Modi, V. J.; Mah, H. W.; Misra, A. K.
This paper aims at development of a rather versatile tool for studying the dynamics and control of an orbiting flexible manipulator. It is motivated by the Canadian contribution, in the form of the mobile servicing system (MSS), to the U.S. led Space Station program, scheduled to be operational by the turn of the century. To begin with, a relatively general dynamical formulation is developed for a large class of systems characterized by interconnected beam and/or rigid articulating members forming a chain-type geometry. As can be expected, the governing non-linear, non-autonomous and coupled equations of motion, extremely long even in matrix notation, are not amenable to any known closed form solution. Hence attention is focused towards development of an efficient numerical code, in a modular format, to help assess the relative importance of the various system parameters. Validity of the formulation and the computer code are assessed and their operational aspects demonstrated through a parametric response analysis. Emphasis throughout is on methodology and general approach leading to understanding of the multibody dynamics problem at the fundamental level. The versatility of the formulation and corresponding code permits dynamical analysis and non-linear control of a wide class of space- and ground-based manipulators. Results suggest that interaction between the Space Station and MSS can lead to undesirable librational and vibrational response for the station. The station response, in turn, may diminish performance of the highly flexible manipulator system. The versatility of the formulation is demonstrated in its application to several other configurations: scientific and communications satellites with flexible beam-type members as well as tethered systems.
Wireless Positioning Based on a Segment-Wise Linear Approach for Modeling the Target Trajectory
DEFF Research Database (Denmark)
Figueiras, Joao; Pedersen, Troels; Schwefel, Hans-Peter
2008-01-01
measurements and the user mobility patterns. One class of typical human being movement patterns is the segment-wise linear approach, which is studied in this paper. Current tracking solutions, such as the Constant Velocity model, hardly handle such segment-wise linear patterns. In this paper we propose...... a segment-wise linear model, called the Drifting Points model. The model results in an increased performance when compared with traditional solutions....
Analysis of fractional non-linear diffusion behaviors based on Adomian polynomials
Directory of Open Access Journals (Sweden)
Wu Guo-Cheng
2017-01-01
Full Text Available A time-fractional non-linear diffusion equation of two orders is considered to investigate strong non-linearity through porous media. An equivalent integral equation is established and Adomian polynomials are adopted to linearize non-linear terms. With the Taylor expansion of fractional order, recurrence formulae are proposed and novel numerical solutions are obtained to depict the diffusion behaviors more accurately. The result shows that the method is suitable for numerical simulation of the fractional diffusion equations of multi-orders.
Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons
Directory of Open Access Journals (Sweden)
Samuel L. Nogueira
2014-01-01
Full Text Available In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF to improve the performance of inertial measurement units (IMUs based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank are not taken into account in other link position estimation (e.g., the foot. In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties.
Downlink Linear Precoders Based on Statistical CSI for Multicell MIMO-OFDM
Directory of Open Access Journals (Sweden)
Ebrahim Baktash
2017-01-01
Full Text Available With 5G communication systems on the horizon, efficient interference management in heterogeneous multicell networks is more vital than ever. This paper investigates the linear precoder design for downlink multicell multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM systems, where base stations (BSs coordinate to reduce the interference across space and frequency. In order to minimize the overall feedback overhead in next-generation systems, we consider precoding schemes that require statistical channel state information (CSI only. We apply the random matrix theory to approximate the ergodic weighted sum rate of the system with a closed form expression. After formulating the approximation for general channels, we reduce the results to a more compact form using the Kronecker channel model for which several multicarrier concepts such as frequency selectivity, channel tap correlations, and intercarrier interference (ICI are rigorously represented. We find the local optimal solution for the maximization of the approximate rate using a gradient method that requires only the covariance structure of the MIMO-OFDM channels. Within this covariance structure are the channel tap correlations and ICI information, both of which are taken into consideration in the precoder design. Simulation results show that the rate approximation is very accurate even for very small MIMO-OFDM systems and the proposed method converges rapidly to a near-optimal solution that competes with networked MIMO and precoders based on instantaneous full CSI.
Long, Yun; Zhang, Yong; Zhang, Xinliang; Xia, Jinsong; Dong, Jianji; Wang, Jian
2017-06-01
We propose and demonstrate an ultracompact bandpass microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) microcavity. Taking the fabricated PhC microcavity as an example, we comprehensively investigate both the linear and nonlinear microwave responses of the MPF based on silicon waveguide devices. Two cases are discussed in the experiment, i.e., the optical carrier wavelength is located on the left or right side of the notch resonant wavelength of the PhC microcavity. The experimental results agree well with the theoretical analyses. For the former case, the central frequency of MPF increases monotonically when fixing the optical carrier wavelength and increasing the optical carrier power. For the latter case, the nonlinear response at a fixed optical carrier wavelength shows a decrease first and then an increase in the central frequency of MPF when increasing the optical carrier power. A jump of the response is observed in the switching process. Moreover, we also observe an interesting bistable microwave response in the experiment under an optical carrier power of around -2.6 dBm in the latter case.
An Ionospheric Index Model based on Linear Regression and Neural Network Approaches
Tshisaphungo, Mpho; McKinnell, Lee-Anne; Bosco Habarulema, John
2017-04-01
The ionosphere is well known to reflect radio wave signals in the high frequency (HF) band due to the present of electron and ions within the region. To optimise the use of long distance HF communications, it is important to understand the drivers of ionospheric storms and accurately predict the propagation conditions especially during disturbed days. This paper presents the development of an ionospheric storm-time index over the South African region for the application of HF communication users. The model will result into a valuable tool to measure the complex ionospheric behaviour in an operational space weather monitoring and forecasting environment. The development of an ionospheric storm-time index is based on a single ionosonde station data over Grahamstown (33.3°S,26.5°E), South Africa. Critical frequency of the F2 layer (foF2) measurements for a period 1996-2014 were considered for this study. The model was developed based on linear regression and neural network approaches. In this talk validation results for low, medium and high solar activity periods will be discussed to demonstrate model's performance.
A Multi-TeV Linear Collider Based on CLIC Technology CLIC Conceptual Design Report
Burrows, P; Draper, M; Garvey, T; Lebrun, P; Peach, K; Phinney, N; Schmickler, H; Schulte, D; Toge, N
2012-01-01
This report describes the accelerator studies for a future multi-TeV e+e- collider based on the Compact Linear Collider (CLIC) technology. The CLIC concept as described in the report is based on high gradient normal-conducting accelerating structures where the RF power for the acceleration of the colliding beams is extracted from a high-current Drive Beam that runs parallel with the main linac. The focus of CLIC R&D over the last years has been on addressing a set of key feasibility issues that are essential for proving the fundamental validity of the CLIC concept. The status of these feasibility studies are described and summarized. The report also includes a technical description of the accelerator components and R&D to develop the most important parts and methods, as well as a description of the civil engineering and technical services associated with the installation. Several larger system tests have been performed to validate the two-beam scheme, and of particular importance are the results from ...
Stephen, Lincy; Yogesh, N.; Subramanian, V.
2018-01-01
The giant optical activity of chiral metamaterials (CMMs) holds great potential for tailoring the polarization state of an electromagnetic (EM) wave. In controlling the polarization state, the aspect of asymmetric transmission (AT), where a medium allows the EM radiation to pass through in one direction while restricting it in the opposite direction, adds additional degrees of freedom such as one-way channelling functionality. In this work, a CMM formed by a pair of mutually twisted slanted complementary metal strips is realized for broadband AT accompanied with cross-polarization (CP) conversion for linearly polarized EM waves. Numerically, the proposed ultra-thin (˜λ/42) CMM shows broadband AT from 8.58 GHz to 9.73 GHz (bandwidth of 1.15 GHz) accompanied with CP transmission magnitude greater than 0.9. The transmission and reflection spectra reveal the origin of the asymmetric transmission as the direction sensitive cross polarization conversion and anisotropic electric coupling occurring in the structure which is then elaborated with the surface current analysis and electric field distribution within the structure. An experiment is carried out to verify the broadband AT based CP conversion of the proposed CMM at microwave frequencies, and a reliable agreement between numerical and experimental results is obtained. Being ultra-thin, the reported broadband AT based CP conversion of the proposed CMM is useful for controlling radiation patterns in non-reciprocal EM devices and communication networks.
A compact linear accelerator based on a scalable microelectromechanical-system RF-structure
Persaud, A.; Ji, Q.; Feinberg, E.; Seidl, P. A.; Waldron, W. L.; Schenkel, T.; Lal, A.; Vinayakumar, K. B.; Ardanuc, S.; Hammer, D. A.
2017-06-01
A new approach for a compact radio-frequency (RF) accelerator structure is presented. The new accelerator architecture is based on the Multiple Electrostatic Quadrupole Array Linear Accelerator (MEQALAC) structure that was first developed in the 1980s. The MEQALAC utilized RF resonators producing the accelerating fields and providing for higher beam currents through parallel beamlets focused using arrays of electrostatic quadrupoles (ESQs). While the early work obtained ESQs with lateral dimensions on the order of a few centimeters, using a printed circuit board (PCB), we reduce the characteristic dimension to the millimeter regime, while massively scaling up the potential number of parallel beamlets. Using Microelectromechanical systems scalable fabrication approaches, we are working on further reducing the characteristic dimension to the sub-millimeter regime. The technology is based on RF-acceleration components and ESQs implemented in the PCB or silicon wafers where each beamlet passes through beam apertures in the wafer. The complete accelerator is then assembled by stacking these wafers. This approach has the potential for fast and inexpensive batch fabrication of the components and flexibility in system design for application specific beam energies and currents. For prototyping the accelerator architecture, the components have been fabricated using the PCB. In this paper, we present proof of concept results of the principal components using the PCB: RF acceleration and ESQ focusing. Ongoing developments on implementing components in silicon and scaling of the accelerator technology to high currents and beam energies are discussed.
Directory of Open Access Journals (Sweden)
Laith K. Abbas
2014-01-01
Full Text Available In this paper, an approach based on transfer matrix method of linear multibody systems (MS-TMM is developed to analyze the free vibration of a multilevel beam, coupled by spring/dashpot systems attached to them in-span. The Euler-Bernoulli model is used for the transverse vibration of the beams, and the spring/dashpot system represents a simplified model of a viscoelastic material. MS-TMM reduces the dynamic problem to an overall transfer equation which only involves boundary state vectors. The state vectors at the boundaries are composed of displacements, rotation angles, bending moments, and shear forces, which are partly known and partly unknown, and end up with reduced overall transfer matrix. Nontrivial solution requires the coefficient matrix to be singular to yield the required natural frequencies. This paper implements two novel algorithms based on the methodology by reducing the zero search of the reduced overall transfer matrix's determinate to a minimization problem and demonstrates a simple and robust algorithm being much more efficient than direct enumeration. The proposal method is easy to formulate, systematic to apply, and simple to code and can be extended to complex structures with any boundary conditions. Numerical results are presented to show the validity of the proposal method against the published literature.
Energy Technology Data Exchange (ETDEWEB)
Patil, B.J., E-mail: bjp@physics.unipune.ac.in [Department of Physics, University of Pune, Pune 411 007 (India); Chavan, S.T.; Pethe, S.N.; Krishnan, R. [SAMEER, IIT Powai Campus, Mumbai 400 076 (India); Bhoraskar, V.N. [Department of Physics, University of Pune, Pune 411 007 (India); Dhole, S.D., E-mail: sanjay@physics.unipune.ac.in [Department of Physics, University of Pune, Pune 411 007 (India)
2012-01-15
The 6 MeV LINAC based pulsed thermal neutron source has been designed for bulk materials analysis. The design was optimized by varying different parameters of the target and materials for each region using FLUKA code. The optimized design of thermal neutron source gives flux of 3 Multiplication-Sign 10{sup 6}ncm{sup -2}s{sup -1} with more than 80% of thermal neutrons and neutron to gamma ratio was 1 Multiplication-Sign 10{sup 4}ncm{sup -2}mR{sup -1}. The results of prototype experiment and simulation are found to be in good agreement with each other. - Highlights: Black-Right-Pointing-Pointer The optimized 6 eV linear accelerator based thermal neutron source using FLUKA simulation. Black-Right-Pointing-Pointer Beryllium as a photonuclear target and reflector, polyethylene as a filter and shield, graphite as a moderator. Black-Right-Pointing-Pointer Optimized pulsed thermal neutron source gives neutron flux of 3 Multiplication-Sign 10{sup 6} n cm{sup -2} s{sup -1}. Black-Right-Pointing-Pointer Results of the prototype experiment were compared with simulations and are found to be in good agreement. Black-Right-Pointing-Pointer This source can effectively be used for the study of bulk material analysis and activation products.
A new standing-wave-type linear ultrasonic motor based on in-plane modes.
Shi, Yunlai; Zhao, Chunsheng
2011-05-01
This paper presents a new standing-wave-type linear ultrasonic motor using combination of the first longitudinal and the second bending modes. Two piezoelectric plates in combination with a metal thin plate are used to construct the stator. The superior point of the stator is its isosceles triangular structure part of the stator, which can amplify the displacement in horizontal direction of the stator in perpendicular direction when the stator is operated in the first longitudinal mode. The influence of the base angle θ of the triangular structure part on the amplitude of the driving foot has been analyzed by numerical analysis. Four prototype stators with different angles θ have been fabricated and the experimental investigation of these stators has validated the numerical simulation. The overall dimensions of the prototype stators are no more than 40 mm (length) × 20 mm (width) × 5 mm (thickness). Driven by an AC signal with the driving frequency of 53.3 kHz, the no-load speed and the maximal thrust of the prototype motor using the stator with base angle 20° were 98 mm/s and 3.2N, respectively. The effective elliptical motion trajectory of the contact point of the stator can be achieved by the isosceles triangular structure part using only two PZTs, and thus it makes the motor low cost in fabrication, simple in structure and easy to realize miniaturization. Copyright © 2010 Elsevier B.V. All rights reserved.
Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds.
Marrero-Ponce, Yovani; Meneses-Marcel, Alfredo; Rivera-Borroto, Oscar M; García-Domenech, Ramón; De Julián-Ortiz, Jesus Vicente; Montero, Alina; Escario, José Antonio; Barrio, Alicia Gómez; Pereira, David Montero; Nogal, Juan José; Grau, Ricardo; Torrens, Francisco; Vogel, Christian; Arán, Vicente J
2008-08-01
Trichomonas vaginalis (Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show
Chang, Chiou-Shiung; Hwang, Jing-Min; Tai, Po-An; Chang, You-Kang; Wang, Yu-Nong; Shih, Rompin; Chuang, Keh-Shih
2016-01-01
Stereotactic radiosurgery (SRS) is a well-established technique that is replacing whole-brain irradiation in the treatment of intracranial lesions, which leads to better preservation of brain functions, and therefore a better quality of life for the patient. There are several available forms of linear accelerator (LINAC)-based SRS, and the goal of the present study is to identify which of these techniques is best (as evaluated by dosimetric outcomes statistically) when the target is located adjacent to brainstem. We collected the records of 17 patients with lesions close to the brainstem who had previously been treated with single-fraction radiosurgery. In all, 5 different lesion catalogs were collected, and the patients were divided into 2 distance groups-1 consisting of 7 patients with a target-to-brainstem distance of less than 0.5cm, and the other of 10 patients with a target-to-brainstem distance of ≥ 0.5 and radiosurgery: dynamic conformal arcs (DCA), intensity-modulated radiosurgery (IMRS), and volumetric modulated arc radiotherapy (VMAT). All techniques included multiple noncoplanar beams or arcs with or without intensity-modulated delivery. The volume of gross tumor volume (GTV) ranged from 0.2cm(3) to 21.9cm(3). Regarding the dose homogeneity index (HIICRU) and conformity index (CIICRU) were without significant difference between techniques statistically. However, the average CIICRU = 1.09 ± 0.56 achieved by VMAT was the best of the 3 techniques. Moreover, notable improvement in gradient index (GI) was observed when VMAT was used (0.74 ± 0.13), and this result was significantly better than those achieved by the 2 other techniques (p < 0.05). For V4Gy of brainstem, both VMAT (2.5%) and IMRS (2.7%) were significantly lower than DCA (4.9%), both at the p < 0.05 level. Regarding V2Gy of normal brain, VMAT plans had attained 6.4 ± 5%; this was significantly better (p < 0.05) than either DCA or IMRS plans, at 9.2 ± 7% and 8.2 ± 6%, respectively. Owing to
Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds
Marrero-Ponce, Yovani; Meneses-Marcel, Alfredo; Rivera-Borroto, Oscar M.; García-Domenech, Ramón; De Julián-Ortiz, Jesus Vicente; Montero, Alina; Escario, José Antonio; Barrio, Alicia Gómez; Pereira, David Montero; Nogal, Juan José; Grau, Ricardo; Torrens, Francisco; Vogel, Christian; Arán, Vicente J.
2008-08-01
Trichomonas vaginalis ( Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients ( C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show
Genomic prediction based on data from three layer lines: a comparison between linear methods
Calus, M.P.L.; Huang, H.; Vereijken, J.; Visscher, J.; Napel, ten J.; Windig, J.J.
2014-01-01
Background The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction. Methods Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we
Directory of Open Access Journals (Sweden)
Sirin Sait
2011-01-01
Full Text Available Background/Aim. Management of patients with recurrent glioblastoma (GB comprises a therapeutic challenge in neurooncology owing to the aggressive nature of the disease with poor local control despite a combined modality treatment. The majority of cases recur within the highdose radiotherapy field limiting the use of conventional techniques for re-irradiation due to potential toxicity. Stereotactic radiosurgery (SRS offers a viable noninvasive therapeutic option in palliative treatment of recurrent GB as a sophisticated modality with improved setup accuracy allowing the administration of high-dose, precise radiotherapy. The aim of the study was to, we report our experience with single-dose linear accelerator (LINAC based SRS in the management of patients with recurrent GB. Methods. Between 1998 and 2010 a total of 19 patients with recurrent GB were treated using single-dose LINAC-based SRS. The median age was 47 (23-65 years at primary diagnosis. Karnofsky Performance Score was ≥ 70 for all the patients. The median planning target volume (PTV was 13 (7-19 cc. The median marginal dose was 16 (10-19 Gy prescribed to the 80%-95% isodose line encompassing the planning target volume. The median follow-up time was 13 (2-59 months. Results. The median survival was 21 months and 9.3 months from the initial GB diagnosis and from SRS, respectively. The median progression-free survival from SRS was 5.7 months. All the patients tolerated radiosurgical treatment well without any Common Toxicity Criteria (CTC grade > 2 acute side effects. Conclusion. Single-dose LINAC-based SRS is a safe and well- tolerated palliative therapeutic option in the management of patients with recurrent GB.
Sager, Omer; Beyzadeoglu, Murat; Dincoglan, Ferrat; Gamsiz, Hakan; Demiral, Selcuk; Uysal, Bora; Oysul, Kaan; Dirican, Bahar; Sirin, Sait
2014-01-01
Although mostly benign and slow-growing, glomus jugulare tumors have a high propensity for local invasion of adjacent vascular structures, lower cranial nerves and the inner ear, which may result in substantial morbidity and even mortality. Treatment strategies for glomus jugulare tumors include surgery, preoperative embolization followed by surgical resection, conventionally fractionated external beam radiotherapy, radiosurgery in the form of stereotactic radiosurgery or fractionated stereotactic radiation therapy, and combinations of these modalities. In the present study, we evaluate the use of linear accelerator (LINAC)-based stereotactic radiosurgery in the management of glomus jugulare tumors and report our 15-year single center experience. Between May 1998 and May 2013, 21 patients (15 females, 6 males) with glomus jugulare tumors were treated using LINAC-based stereotactic radiosurgery at the Department of Radiation Oncology, Gulhane Military Medical Academy. The indication for stereotactic radiosurgery was the presence of residual or recurrent tumor after surgery for 5 patients, whereas 16 patients having growing tumors with symptoms received stereotactic radiosurgery as the primary treatment. Median follow-up was 49 months (range, 3-98). Median age was 55 years (range, 24-77). Of the 21 lesions treated, 13 (61.9%) were left-sided and 8 (38.1%) were right-sided. Median dose was 15 Gy (range, 10-20) prescribed to the 85%-100% isodose line encompassing the target volume. Local control defined as either tumor shrinkage or the absence of tumor growth on periodical follow-up neuroimaging was 100%. LINAC-based stereotactic radiosurgery offers a safe and efficacious management strategy for glomus jugulare tumors by providing excellent tumor growth control with few complications.
Linear transformation based orthotropic shear ductile fracture criterion for lightweight metals
Lou, Yanshan; Yoon, Jeong Whan
2017-10-01
Accurate modelling of orthotropic ductile fracture is key to carry out reliable numerical prediction of rupture in plastic deformation of lightweight metals, such as ultra high strength steel, aluminum alloys, titanium alloys and magnesium alloys. Experiments are conducted for an aluminum alloy in shear, uniaxial tension, plane strain tension along rolling direction, diagonal direction and transverse direction as well as the balanced biaxial tension of the Nakajima test. Loading processes are recorded and fracture strain is measured by analysis of deformation with digital image correlation. Fracture behavior is modelled by a shear ductile fracture criterion of DF2016 along different loading directions. It is observed that anisotropy in ductile fracture cannot be correctly described by an isotropic ductile fracture criterion. Thus, an anisotropic ductile fracture criterion is proposed from a shear ductile fracture criterion of DF2014 based on linear transformation of the plastic strain vector into an isotropic equivalent damage strain vector. The anisotropic ductile fracture criterion is applied to model orthotropic fracture strain in shear, uniaxial tension and plane strain tension. The predicted anisotropy in ductile fracture is compared with experimental results for the verification of its accuracy. The comparison indicates that the proposed anisotropic ductile fracture criterion accurately models orthotropic ductile fracture in various loading conditions in shear, uniaxial tension and plane strain tension.
Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems
Suliman, Mohamed Abdalla Elhag
2016-11-29
Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.
Sun, L; Xu, J-C; Wang, W; Yin, Y
2016-08-30
Cancer subtype recognition and feature selection are important problems in the diagnosis and treatment of tumors. Here, we propose a novel gene selection approach applied to gene expression data classification. First, two classical feature reduction methods including locally linear embedding (LLE) and rough set (RS) are summarized. The advantages and disadvantages of these algorithms were analyzed and an optimized model for tumor gene selection was developed based on LLE and neighborhood RS (NRS). Bhattacharyya distance was introduced to delete irrelevant genes, pair-wise redundant analysis was performed to remove strongly correlated genes, and the wavelet soft threshold was determined to eliminate noise in the gene datasets. Next, prior optimized search processing was carried out. A new approach combining dimension reduction of LLE and feature reduction of NRS (LLE-NRS) was developed for selecting gene subsets, and then an open source software Weka was applied to distinguish different tumor types and verify the cross-validation classification accuracy of our proposed method. The experimental results demonstrated that the classification performance of the proposed LLE-NRS for selecting gene subset outperforms those of other related models in terms of accuracy, and our proposed approach is feasible and effective in the field of high-dimensional tumor classification.
Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer
2016-06-02
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Energy Technology Data Exchange (ETDEWEB)
Mao, Jinlong; Zuo, Zhengxing; Li, Wen; Feng, Huihua [School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081 (China)
2011-04-15
A free-piston linear alternator (FPLA) is being developed by the Beijing Institute of Technology to improve the thermal efficiency relative to conventional crank-driven engines. A two-stroke scavenging process recharges the engine and is crucial to realizing the continuous operation of a free-piston engine. In order to study the FPLA scavenging process, the scavenging system was configured using computational fluid dynamics. As the piston dynamics of the FPLA are different to conventional crank-driven two-stroke engines, a time-based numerical simulation program was built using Matlab to define the piston's motion profiles. A wide range of design and operating options were investigated including effective stroke length, valve overlapping distance, operating frequency and charging pressure to find out their effects on the scavenging performance. The results indicate that a combination of high effective stroke length to bore ratio and long valve overlapping distance with a low supercharging pressure has the potential to achieve high scavenging and trapping efficiencies with low short-circuiting losses. (author)
Dasgupta, Queeny; Movva, Sahitya; Chatterjee, Kaushik; Madras, Giridhar
2017-08-07
This work reports the synthesis of a novel, aspirin-loaded, linear poly (anhydride ester) and provides mechanistic insights into the release of aspirin from this polymer for anti-inflammatory activity. As compared to conventional drug delivery systems that rely on diffusion based release, incorporation of bioactives in the polymer backbone is challenging and high loading is difficult to achieve. In the present study, we exploit the pentafunctional sugar alcohol (xylitol) to provide sites for drug (aspirin) attachment at its non-terminal OH groups. The terminal OH groups are polymerized with a diacid anhydride. The hydrolysis of the anhydride and ester bonds under physiological conditions release aspirin from the matrix. The resulting poly(anhydride ester) has high drug loading (53%) and displays controlled release kinetics of aspirin. The polymer releases 8.5 % and 20%, of the loaded drug in one and four weeks, respectively and has a release rate constant of 0.0035h -0.61 . The release rate is suitable for its use as an anti-inflammatory agent without being cytotoxic. The polymer exhibits good cytocompatibility and anti-inflammatory properties and may find applications as injectable or as an implantable bioactive material. The physical insights into the release mechanism can provide development of other drug loaded polymers. Copyright © 2017 Elsevier B.V. All rights reserved.
Linear redshift space distortions for cosmic voids based on galaxies in redshift space
Chuang, Chia-Hsun; Kitaura, Francisco-Shu; Liang, Yu; Font-Ribera, Andreu; Zhao, Cheng; McDonald, Patrick; Tao, Charling
2017-03-01
Cosmic voids found in galaxy surveys are defined based on the galaxy distribution in redshift space. We show that the large scale distribution of voids in redshift space traces the fluctuations in the dark matter density field δ(k) (in Fourier space with μ being the line of sight projected k-vector): δ_v^s(k) = (1 + β_v μ^2) b^s_v δ(k), with a beta factor that will be in general different than the one describing the distribution of galaxies. Only in case voids could be assumed to be quasi-local transformations of the linear (Gaussian) galaxy redshift space field, one gets equal beta factors β_v=β_g=f/b_g with f being the growth rate, and b_g, b^s_v being the galaxy and void bias on large scales defined in redshift space. Indeed, in our mock void catalogs we measure void beta factors being in good agreement with the galaxy one. Further work needs to be done to confirm the level of accuracy of the beta factor equality between voids and galaxies, but in general the void beta factor needs to be considered as a free parameter for RSD studies.
Counter-propagating dual-trap optical tweezers based on linear momentum conservation
Energy Technology Data Exchange (ETDEWEB)
Ribezzi-Crivellari, M.; Huguet, J. M. [Small Biosystems Lab, Dept. de Fisica Fonamental, Universitat de Barcelona, Avda. Diagonal 647, 08028 Barcelona (Spain); Ritort, F. [Small Biosystems Lab, Dept. de Fisica Fonamental, Universitat de Barcelona, Avda. Diagonal 647, 08028 Barcelona (Spain); Ciber-BBN de Bioingenieria, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid (Spain)
2013-04-15
We present a dual-trap optical tweezers setup which directly measures forces using linear momentum conservation. The setup uses a counter-propagating geometry, which allows momentum measurement on each beam separately. The experimental advantages of this setup include low drift due to all-optical manipulation, and a robust calibration (independent of the features of the trapped object or buffer medium) due to the force measurement method. Although this design does not attain the high-resolution of some co-propagating setups, we show that it can be used to perform different single molecule measurements: fluctuation-based molecular stiffness characterization at different forces and hopping experiments on molecular hairpins. Remarkably, in our setup it is possible to manipulate very short tethers (such as molecular hairpins with short handles) down to the limit where beads are almost in contact. The setup is used to illustrate a novel method for measuring the stiffness of optical traps and tethers on the basis of equilibrium force fluctuations, i.e., without the need of measuring the force vs molecular extension curve. This method is of general interest for dual trap optical tweezers setups and can be extended to setups which do not directly measure forces.
Correction of TRMM 3B42V7 Based on Linear Regression Models over China
Directory of Open Access Journals (Sweden)
Shaohua Liu
2016-01-01
Full Text Available High temporal-spatial precipitation is necessary for hydrological simulation and water resource management, and remotely sensed precipitation products (RSPPs play a key role in supporting high temporal-spatial precipitation, especially in sparse gauge regions. TRMM 3B42V7 data (TRMM precipitation is an essential RSPP outperforming other RSPPs. Yet the utilization of TRMM precipitation is still limited by the inaccuracy and low spatial resolution at regional scale. In this paper, linear regression models (LRMs have been constructed to correct and downscale the TRMM precipitation based on the gauge precipitation at 2257 stations over China from 1998 to 2013. Then, the corrected TRMM precipitation was validated by gauge precipitation at 839 out of 2257 stations in 2014 at station and grid scales. The results show that both monthly and annual LRMs have obviously improved the accuracy of corrected TRMM precipitation with acceptable error, and monthly LRM performs slightly better than annual LRM in Mideastern China. Although the performance of corrected TRMM precipitation from the LRMs has been increased in Northwest China and Tibetan plateau, the error of corrected TRMM precipitation is still significant due to the large deviation between TRMM precipitation and low-density gauge precipitation.
A combinatorial chemistry approach to new materials for non-linear optics. I. Five schiff bases
Nesterov; Timofeeva; Borbulevych; Antipin; Clark
2000-08-01
A combinatorial chemistry approach has been used to synthesize an array of Schiff bases, five of which, namely N-[(E, 2E)-3-(4-methoxyphenyl)-2-propenylidene]-3-nitroaniline, C(16)H(14)N(2)O(3), (1a), N-[(E, 2E)-3-(4-methoxyphenyl)-2-propenylidene]-4-nitroaniline, C(16)H(14)N(2)O(3), (2a), N-(E, 2E)-3-[4-(dimethylamino)phenyl]-2-propenylidene-3-nitroaniline, C(17)H(17)N(3)O(2), (1b), N-(E, 2E)-3-[4-(dimethylamino)phenyl]-2-propenylidene-4-nitroaniline, C(17)H(17)N(3)O(2), (2b), and N-(E, 2E)-3-[4-(dimethylamino)phenyl]-2-propenylidene-2-methyl-4-nitroanil ine, C(18)H(19)N(3)O(2), (3b), have been structurally characterized. A stack structure is observed for (1a) and (1b) in the crystal phase. Experimental and calculated molecular structures are discussed for these compounds which belong to a chemical class having potential applications as non-linear optical materials.
Beyond simple linear mixing models: process-based isotope partitioning of ecological processes.
Ogle, Kiona; Tucker, Colin; Cable, Jessica M
2014-01-01
Stable isotopes are valuable tools for partitioning the components contributing to ecological processes of interest, such as animal diets and trophic interactions, plant resource use, ecosystem gas fluxes, streamflow, and many more. Stable isotope data are often analyzed with simple linear mixing (SLM) models to partition the contributions of different sources, but SLM models cannot incorporate a mechanistic understanding of the underlying processes and do not accommodate additional data associated with these processes (e.g., environmental covariates, flux data, gut contents). Thus, SLM models lack predictive ability. We describe a process-based mixing (PBM) model approach for integrating stable isotopes, other data sources, and process models to partition different sources or process components. This is accomplished via a hierarchical Bayesian framework that quantifies multiple sources of uncertainty and enables the incorporation of process models and prior information to help constrain the source-specific proportional contributions, thereby potentially avoiding identifiability issues that plague SLM models applied to "too many" sources. We discuss the application of the PBM model framework to three diverse examples: temporal and spatial partitioning of streamflow, estimation of plant rooting profiles and water uptake profiles (or water sources) with extension to partitioning soil and ecosystem CO2 fluxes, and reconstructing animal diets. These examples illustrate the advantages of the PBM modeling approach, which facilitates incorporation of ecological theory and diverse sources of information into the mixing model framework, thus enabling one to partition key process components across time and space.
Optimal planning of gas turbine cogeneration system based on linear programming
Energy Technology Data Exchange (ETDEWEB)
Oh, S.D. [Hyosung Corp., Seoul (Korea, Republic of); Kwak, H.Y. [Chung-Ang Univ., Seoul (Korea, Republic of). Dept. of Mechanical Engineering
2005-07-01
Cogeneration systems can result in significant energy efficiency improvements because they produce electrical and heat energy simultaneously from a single source of fuel. This paper discussed planning and design optimization practices for the successful application of a gas turbine cogeneration plant in a hotel and a public building. It was suggested that planners should determine the optimal plant configuration by first selecting the size and number of auxiliary equipment, as well as considering annual electricity costs and heat and cooling requirements. An optimal planning method was presented, employing system configurations among possible combinations of equipment, operational plans and energy demand patterns. A mixed-integer linear program and branch and bound algorithms were adapted to obtain the optimal configuration, based on an annual cost method. A public building and a hotel in Seoul, Korea were selected as case studies. Energy demand patterns for both buildings were presented, with details of maximum outputs and initial equipment costs for co-generation plants. Payback periods and internal rates of return were examined. It was concluded that the optimal configuration of the cogeneration plant is determined by considering the annual energy demand patterns of both buildings, as these patterns are a crucial parameter in determining the feasibility of a cogeneration plant. It was suggested that the methods presented in this study may provide the best configuration of a cogeneration plant fitted to a hotel, or public buildings. 6 refs., 9 tabs., 6 figs.
Outlier Detection Method in Linear Regression Based on Sum of Arithmetic Progression
Directory of Open Access Journals (Sweden)
K. K. L. B. Adikaram
2014-01-01
Full Text Available We introduce a new nonparametric outlier detection method for linear series, which requires no missing or removed data imputation. For an arithmetic progression (a series without outliers with n elements, the ratio (R of the sum of the minimum and the maximum elements and the sum of all elements is always 2/n:(0,1]. R≠2/n always implies the existence of outliers. Usually, R2/n implies that the maximum is an outlier. Based upon this, we derived a new method for identifying significant and nonsignificant outliers, separately. Two different techniques were used to manage missing data and removed outliers: (1 recalculate the terms after (or before the removed or missing element while maintaining the initial angle in relation to a certain point or (2 transform data into a constant value, which is not affected by missing or removed elements. With a reference element, which was not an outlier, the method detected all outliers from data sets with 6 to 1000 elements containing 50% outliers which deviated by a factor of ±1.0e-2 to ±1.0e+2 from the correct value.
Directory of Open Access Journals (Sweden)
Sergei Vladimirovich Varaksin
2017-06-01
Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.
DEFF Research Database (Denmark)
Barreras, Jorge Varela; Pinto, Claudio; de Castro, Ricardo
2015-01-01
in the context of energy management or sizing problem of energy storage systems. In this paper, an improved parametrization method for Li-ion linear static EECMs based on the so called concept of direct current resistance (DCR) is presented. By drawing on a DCR-based parametrization, the influence of both...
Kim, Jiwoong; Ahn, Yongju; Lee, Kichan; Park, Sung Hee; Kim, Sangsoo
2010-08-21
Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query sequence based on the statistical genotype models learned from the known sequences. Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment. MuLDAS starts by aligning the query sequence to the reference multiple sequence alignment and calculating the subsequent distance matrix among the sequences. They are then mapped to a principal coordinate space by multidimensional scaling, and the coordinates of the reference sequences are used as features in developing linear discriminant models that partition the space by genotype. The genotype of the query is then given as the maximum a posteriori estimate. MuLDAS tests the model confidence by leave-one-out cross-validation and also provides some heuristics for the detection of 'outlier' sequences that fall far outside or in-between genotype clusters. We have tested our method by classifying HIV-1 and HCV nucleotide sequences downloaded from NCBI GenBank, achieving the overall concordance rates of 99.3% and 96.6%, respectively, with the benchmark test dataset retrieved from the respective databases of Los Alamos National Laboratory. The highly accurate genotype assignment coupled with several measures for evaluating the results makes MuLDAS useful in analyzing the sequences of rapidly evolving viruses such as HIV-1 and HCV. A web-based genotype prediction server is available at http://www.muldas.org/MuLDAS/.
Fushimi, Akihiro; Kawashima, Hiroto; Kajihara, Hideo
Understanding the contribution of each emission source of air pollutants to ambient concentrations is important to establish effective measures for risk reduction. We have developed a source apportionment method based on an atmospheric dispersion model and multiple linear regression analysis (MLR) in conjunction with ambient concentrations simultaneously measured at points in a grid network. We used a Gaussian plume dispersion model developed by the US Environmental Protection Agency called the Industrial Source Complex model (ISC) in the method. Our method does not require emission amounts or source profiles. The method was applied to the case of benzene in the vicinity of the Keiyo Central Coastal Industrial Complex (KCCIC), one of the biggest industrial complexes in Japan. Benzene concentrations were simultaneously measured from December 2001 to July 2002 at sites in a grid network established in the KCCIC and the surrounding residential area. The method was used to estimate benzene emissions from the factories in the KCCIC and from automobiles along a section of a road, and then the annual average contribution of the KCCIC to the ambient concentrations was estimated based on the estimated emissions. The estimated contributions of the KCCIC were 65% inside the complex, 49% at 0.5-km sites, 35% at 1.5-km sites, 20% at 3.3-km sites, and 9% at a 5.6-km site. The estimated concentrations agreed well with the measured values. The estimated emissions from the factories and the road were slightly larger than those reported in the first Pollutant Release and Transfer Register (PRTR). These results support the reliability of our method. This method can be applied to other chemicals or regions to achieve reasonable source apportionments.
Mendenhall, Jonathan D.
's and other micellization properties for a variety of linear and branched surfactant chemical architectures which are commonly encountered in practice. Single-component surfactant solutions are investigated, in order to clarify the specific contributions of the surfactant head and tail to the free energy of micellization, a quantity which determines the cmc and all other aspects of micellization. First, a molecular-thermodynamic (MT) theory is presented which makes use of bulk-phase thermodynamics and a phenomenological thought process to describe the energetics related to the formation of a micelle from its constituent surfactant monomers. Second, a combined computer-simulation/molecular-thermodynamic (CSMT) framework is discussed which provides a more detailed quantification of the hydrophobic effect using molecular dynamics simulations. A novel computational strategy to identify surfactant head and tail using an iterative dividing surface approach, along with simulated micelle results, is proposed. Force-field development for novel surfactant structures is also discussed. Third, a statistical-thermodynamic, single-chain, mean-field theory for linear and branched tail packing is formulated, which enables quantification of the specific energetic penalties related to confinement and constraint of surfactant tails within micelles. Finally, these theoretical and simulations-based strategies are used to predict the micellization behavior of 55 linear surfactants and 28 branched surfactants. Critical micelle concentration and optimal micelle properties are reported and compared with experiment, demonstrating good agreement across a range of surfactant head and tail types. In particular, the CSMT framework is found to provide improved agreement with experimental cmc's for the branched surfactants considered. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)
Methodology and Applications in Non-linear Model-based Geostatistics
DEFF Research Database (Denmark)
Christensen, Ole Fredslund
that are approximately Gaussian. Parameter estimation and prediction for the transformed Gaussian model is studied. In some cases a transformation cannot possibly render the data Gaussian. A methodology for analysing such data was introduced by Diggle, Tawn and Moyeed (1998): The generalised linear spatial model....... Conditioned by an underlying and unobserved Gaussian process the observations at the measured locations follow a generalised linear model. Concerning inference Markov chain Monte Carlo methods are used. The study of these models is the main topic of the thesis. Construction of priors, and the use of flat...... contains functions for inference in generalised linear spatial models. ...
Methodology and applications in non-linear model-based geostatistics
DEFF Research Database (Denmark)
Christensen, Ole Fredslund
that are approximately Gaussian. Parameter estimation and prediction for the transformed Gaussian model is studied. In some cases a transformation cannot possibly render the data Gaussian. A methodology for analysing such data was introduced by Diggle, Tawn and Moyeed (1998): The generalised linear spatial model....... Conditioned by an underlying and unobserved Gaussian process the observations at the measured locations follow a generalised linear model. Concerning inference Markov chain Monte Carlo methods are used. The study of these models is the main topic of the thesis. Construction of priors, and the use of flat...... contains functions for inference in generalised linear spatial models. ...
Wagner, Daniel Robert
Linear matrix inequalities and convex optimization techniques have become popular tools to solve nontrivial problems in the field of adaptive control. Specifically, the stability of adaptive control laws in the presence of actuator dynamics remains as an important open control problem. In this thesis, we present a linear matrix inequalities-based hedging approach and evaluate it for model reference adaptive control of an uncertain dynamical system in the presence of actuator dynamics. The ideal reference dynamics are modified such that the hedging approach allows the correct adaptation without being hindered by the presence of actuator dynamics. The hedging approach is first generalized such that two cases are considered where the actuator output and control effectiveness are known and unknown. We then show the stability of the closed-loop dynamical system using Lyapunov based stability analysis tools and propose a linear matrix inequality-based framework for the computation of the minimum allowable actuator bandwidth limits such that the closed-loop dynamical system remains stable. The results of the linear matrix inequality-based heading approach are then generalized to multiactuator systems with a new linear matrix inequality condition. The minimum actuator bandwidth solutions for closed-loop system stability are theoretically guaranteed to exist in a convex set with a partially convex constraint and then solved numerically using an algorithm in the case where there are multiple actuators. Finally, the efficacy of the results contained in this thesis are demonstrated using several illustrative numerical examples.
Cost Cumulant-Based Control for a Class of Linear Quadratic Tracking Problems
National Research Council Canada - National Science Library
Pham, Khanh D
2007-01-01
.... For instance, the present paper extends the application of cost-cumulant controller design to control of a wide class of linear-quadratic tracking systems where output measurements of a tracker...
Multiple-Access Technology of Choice In 3GPP LTE
Directory of Open Access Journals (Sweden)
Ibikunle Frank
2013-09-01
Full Text Available Third-Generation Partnership Project (3GPP standardizes an Evolved UMTS Terrestrial Radio Access Network (E-UTRAN as air interface in its release 8 LTE. Orthogonal Frequency Division Multiple Access(OFDMA and Single Carrier-Frequency Division Multiple Access(SC-FDMAare key technologies for the air interface of mobile broadband systems.It is evident that mobile broadband access technologies are reaching a commonality in the air interface and networking architecture; they are being converged to an IP-based network architecture with OFDMA based air interface technology. The air interface of E-UTRAN is based on OFDMA in downlink and SC-FDMA in the uplink, making it possible to efficiently utilize bandwidth due to the orthogonally between sub-carriers and by assigning subsets of sub-carriers to individual users which allows for simultaneous data rate transmission from several users and differentiated quality of service for each user. In this paper, wehighlight the technologies behindOFDMA and SC-FDMA and also carry out performance comparison of the two air interface technologies. We brieflydescribe the 3GPP LTE standard, and its implementation using OFDMA and SC-FDMA technology.
Circuits and systems based on delta modulation linear, nonlinear and mixed mode processing
Zrilic, Djuro G
2005-01-01
This book is intended for students and professionals who are interested in the field of digital signal processing of delta-sigma modulated sequences. The overall focus is on the development of algorithms and circuits for linear, non-linear, and mixed mode processing of delta-sigma modulated pulse streams. The material presented here is directly relevant to applications in digital communication, DSP, instrumentation, and control.
Fuse, Shinichiro; Mifune, Yuto; Nakamura, Hiroyuki; Tanaka, Hiroshi
2016-11-01
Feglymycin is a naturally occurring, anti-HIV and antimicrobial 13-mer peptide that includes highly racemizable 3,5-dihydroxyphenylglycines (Dpgs). Here we describe the total synthesis of feglymycin based on a linear/convergent hybrid approach. Our originally developed micro-flow amide bond formation enabled highly racemizable peptide chain elongation based on a linear approach that was previously considered impossible. Our developed approach will enable the practical preparation of biologically active oligopeptides that contain highly racemizable amino acids, which are attractive drug candidates.
Liang, Bin; Li, Yongbao; Ran, Wei; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2017-11-17
With robot-controlled linac positioning, the robotic radiotherapy system such as CyberKnife significantly increases the freedom in radiation beam placement, but also imposes more challenges on treatment plan optimization. The resampling mechanism in vendor supplied treatment planning system (MultiPlan) could not fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve the treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam taper. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of treatment plan is achieved by compressive sensing. The proposed liner programming (LP) model optimizes beam weight by minimizing the deviation of soft constraints while subjecting to hard constraints, with the constraint on the l^{1} norm of beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weight of remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. And the beam reduction achieves similar plan quality as the globally optimal plan obtained by MIP model, but is 1-2 orders of magnitude faster. Furthermore, the SVDLP approach
Directory of Open Access Journals (Sweden)
E. E. Tsiropoulou
2016-06-01
Full Text Available In this paper a joint resource allocation problem is studied in a multi-service Single Carrier FDMA (SC-FDMA wireless network. Mobile users request various services with different Quality of Service (QoS characteristics and they determine in a distributed and non-cooperative manner a joint subcarrier and power allocation towards fulfilling their QoS prerequisites. Initially, a well-designed utility function is formulated to appropriately represent users’ diverse QoS prerequisites with respect to their requested service. The subcarriers allocation problem is solved based on a multilateral bargaining model, where users are able to select different discount factors to enter the bargaining game, thus better expressing their different needs in system resources with respect to their requested service. The subcarriers mapping is realized based either on the localized SC-FDMA method where the subcarriers are sequentially allocated to the users or the distributed SC-FDMA via considering the maximum channel gain policy, where each subcarrier is allocated to the user with the maximum channel gain. Given the subcarriers assignment, an optimization problem with respect to users’ uplink transmission power is formulated and solved, in order to determine the optimal power allocation per subcarrier assigned to each user. Finally, the performance of the proposed framework is evaluated via modeling and simulation and extensive numerical results are presented.
Linear accelerator-based stereotactic radiosurgery in 140 brain metastases from malignant melanoma.
Hauswald, Henrik; Stenke, Alina; Debus, Jürgen; Combs, Stephanie E
2015-07-23
To retrospectively access outcome and prognostic parameters of linear accelerator-based stereotactic radiosurgery in brain metastases from malignant melanoma. Between 1990 and 2011 140 brain metastases in 84 patients with malignant melanoma (median age 56 years) were treated with stereotactic radiosurgery. At initial stereotactic radiosurgery 48 % of patients showed extracerebral control. The median count of brain metastases in a single patient was 1, the median diameter was 12 mm. The median dose applied was 20 Gy/80 % isodose enclosing. The median follow-up was 7 months and the median overall survival 9 months. The 6-, 12- and 24 month overall survival rates were 71 %, 39 % and 25 % respectively. Cerebral follow-up imaging showed complete remission in 20 brain metastases, partial remission in 39 brain metastases, stable disease in 54 brain metastases, progressive disease in 24 brain metastases and pseudo-progression in 3 brain metastases. Median intracerebral control was 5.3 months and the 6- and 12-month intracerebral progression-free survival rates 48 % and 38 %, respectively. Upon univariate analysis, extracerebral control (log-rank, p stereotactic radiosurgery (log-rank, p stereotactic radiosurgery high dose region. Stereotactic radiosurgery is a well-tolerated and effective treatment option for brain metastases in malignant melanoma and was able to achieve local remissions in several cases. Furthermore, especially patients with controlled extracerebral disease and a low count of brain metastases seem to benefit from this treatment modality. Prospective trials analysing the effects of combined stereotactic radiosurgery and new systemic agents are warranted.
Group-Based Alternating Direction Method of Multipliers for Distributed Linear Classification.
Wang, Huihui; Gao, Yang; Shi, Yinghuan; Wang, Ruili
2017-11-01
The alternating direction method of multipliers (ADMM) algorithm has been widely employed for distributed machine learning tasks. However, it suffers from several limitations, e.g., a relative low convergence speed, and an expensive time cost. To this end, in this paper, a novel method, namely the group-based ADMM (GADMM), is proposed for distributed linear classification. In particular, to accelerate the convergence speed and improve global consensus, a group layer is first utilized in GADMM to divide all the slave nodes into several groups. Then, all the local variables (from the slave nodes) are gathered in the group layer to generate different group variables. Finally, by using a weighted average method, the group variables are coordinated to update the global variable (from the master node) until the solution of the global problem is reached. According to the theoretical analysis, we found that: 1) GADMM can mathematically converge at the rate , where is the number of outer iterations and 2) by using the grouping methods, GADMM can improve the convergence speed compared with the distributed ADMM framework without grouping methods. Moreover, we systematically evaluate GADMM on four publicly available LIBSVM datasets. Compared with disADMM and stochastic dual coordinate ascent with alternating direction method of multipliers-ADMM, for distributed classification, GADMM is able to reduce the number of outer iterations, which leads to faster convergence speed and better global consensus. In particular, the statistical significance test has been experimentally conducted and the results validate that GADMM can significantly save up to 30% of the total time cost (with less than 0.6% accuracy loss) compared with disADMM on large-scale datasets, e.g., webspam and epsilon.
Tharrey, Marion; Olaya, Gilma A; Fewtrell, Mary; Ferguson, Elaine
2017-12-01
The aim of the study was to use linear programming (LP) analyses to adapt New Complementary Feeding Guidelines (NCFg) designed for infants aged 6 to 12 months living in poor socioeconomic circumstances in Bogota to ensure dietary adequacy for young children aged 12 to 23 months. A secondary data analysis was performed using dietary and anthropometric data collected from 12-month-old infants (n = 72) participating in a randomized controlled trial. LP analyses were performed to identify nutrients whose requirements were difficult to achieve using local foods as consumed; and to test and compare the NCFg and alternative food-based recommendations (FBRs) on the basis of dietary adequacy, for 11 micronutrients, at the population level. Thiamine recommended nutrient intakes for these young children could not be achieved given local foods as consumed. NCFg focusing only on meat, fruits, vegetables, and breast milk ensured dietary adequacy at the population level for only 4 micronutrients, increasing to 8 of 11 modelled micronutrients when the FBRs promoted legumes, dairy, vitamin A-rich vegetables, and chicken giblets. None of the FBRs tested ensured population-level dietary adequacy for thiamine, niacin, and iron unless a fortified infant food was recommended. The present study demonstrated the value of using LP to adapt NCFg for a different age group than the one for which they were designed. Our analyses suggest that to ensure dietary adequacy for 12- to 23-month olds these adaptations should include legumes, dairy products, vitamin A-rich vegetables, organ meat, and a fortified food.
Energy Technology Data Exchange (ETDEWEB)
Matsuo, Takayuki, E-mail: takayuki@nagasaki-u.ac.jp; Kamada, Kensaku; Izumo, Tsuyoshi; Hayashi, Nobuyuki; Nagata, Izumi
2014-07-01
Purpose: Although radiosurgery is an accepted treatment method for intracranial arteriovenous malformations (AVMs), its long-term therapeutic effects have not been sufficiently evaluated, and many reports of long-term observations are from gamma-knife facilities. Furthermore, there are few reported results of treatment using only linear accelerator (LINAC)-based radiosurgery (LBRS). Methods and Materials: Over a period of more than 12 years, we followed the long-term results of LBRS treatment performed in 51 AVM patients. Results: The actuarial obliteration rates, after a single radiosurgery session, at 3, 5, 10, and 15 years were 46.9%, 54.0%, 64.4%, and 68.0%, respectively; when subsequent radiosurgeries were included, the rates were 46.9%, 61.3%, 74.2%, and 90.3%, respectively. Obliteration rates were significantly related to target volumes ≥4 cm{sup 3}, marginal doses ≥12 Gy, Spetzler-Martin grades (1 vs other), and AVM scores ≥1.5; multivariate analyses revealed a significant difference for target volumes ≥4 cm{sup 3}. The postprocedural actuarial symptomatic radiation injury rates, after a single radiation surgery session, at 5, 10, and 15 years were 12.3%, 16.8%, and 19.1%, respectively. Volumes ≥4 cm{sup 3}, location (lobular or other), AVM scores ≥1.5, and the number of radiosurgery were related to radiation injury incidence; multivariate analyses revealed significant differences associated with volumes ≥4 cm{sup 3} and location (lobular or other). Conclusions: Positive results can be obtained with LBRS when performed with a target volume ≤4 cm{sup 3}, an AVM score ≤1.5, and ≥12 Gy radiation. Bleeding and radiation injuries may appear even 10 years after treatment, necessitating long-term observation.
Interlink Converter with Linear Quadratic Regulator Based Current Control for Hybrid AC/DC Microgrid
Directory of Open Access Journals (Sweden)
Dwi Riana Aryani
2017-11-01
Full Text Available A hybrid alternate current/direct current (AC/DC microgrid consists of an AC subgrid and a DC subgrid, and the subgrids are connected through the interlink bidirectional AC/DC converter. In the stand-alone operation mode, it is desirable that the interlink bidirectional AC/DC converter manages proportional power sharing between the subgrids by transferring power from the under-loaded subgrid to the over-loaded one. In terms of system security, the interlink bidirectional AC/DC converter takes an important role, so proper control strategies need to be established. In addition, it is assumed that a battery energy storage system is installed in one subgrid, and the coordinated control of interlink bidirectional AC/DC converter and battery energy storage system converter is required so that the power sharing scheme between subgrids becomes more efficient. For the purpose of designing a tracking controller for the power sharing by interlink bidirectional AC/DC converter in a hybrid AC/DC microgrid, a droop control method generates a power reference for interlink bidirectional AC/DC converter based on the deviation of the system frequency and voltages first and then interlink bidirectional AC/DC converter needs to transfer the power reference to the over-loaded subgrid. For efficiency of this power transferring, a linear quadratic regulator with exponential weighting for the current regulation of interlink bidirectional AC/DC converter is designed in such a way that the resulting microgrid can operate robustly against various uncertainties and the power sharing is carried out quickly. Simulation results show that the proposed interlink bidirectional AC/DC converter control strategy provides robust and efficient power sharing scheme between the subgrids without deteriorating the secure system operation.
Yu, Shao-De; Wu, Shi-Bin; Wang, Hao-Yu; Wei, Xin-Hua; Chen, Xin; Pan, Wan-Long; Hu, Jiani; Xie, Yao-Qin
2015-12-01
Similarity coefficient mapping (SCM) aims to improve the morphological evaluation of weighted magnetic resonance imaging However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM? The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multi-echo . Generated maps were investigated from signal-to-noise ratio (SNR) and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation. Project supported in part by the National High Technology Research and Development Program of China (Grant Nos. 2015AA043203 and 2012AA02A604), the National Natural Science Foundation of China (Grant Nos. 81171402, 61471349, and 81501463), the Innovative Research Team Program of Guangdong Province, China (Grant No. 2011S013), the Science and Technological Program for Higher Education, Science and Research, and Health Care Institutions of Guangdong Province, China (Grant No. 2011108101001), the Natural Science Foundation of Guangdong Province, China (Grant No. 2014A030310360), the Fundamental Research Program of Shenzhen City, China (Grant No. JCYJ20140417113430639), and Beijing Center for Mathematics and Information Interdisciplinary Sciences, China.
National Research Council Canada - National Science Library
Jing Ke;Hanfei Dou;Ximin Zhang;Dushimabararezi Serge Uhagaze;Xiali Ding;Yuming Dong
2016-01-01
.... The dissociation constants of alendronate sodium were determined in this work by studying the piecewise linear relationship between volume of titrant and pH value based on acidbase potentiometric titration reaction...
Sira-Ramírez, H.; Luviano-Juárez, A.; Cortés-Romero, J.
2012-05-01
A linear output feedback controller is developed for trajectory tracking problems defined on a modified version of Chua's circuit. The circuit modification considers the introduction of a flat input, i.e. a suitable external control input channel guided by (a) the induction of the flatness property on a measurable output signal of the circuit and (b) the physical viability of the control input. A linear active disturbance rejection control based on a high-gain linear disturbance observer, is implemented on a laboratory prototype. We show that the state-dependent disturbance can be approximately, but arbitrarily closely, estimated through a linear high-gain observer, called a generalised proportional integral (GPI) observer, which contains a linear combination of a sufficient number of extra iterated integrals of the output estimation error. Experimental results are presented in the output reference trajectory tracking of a signal generated by an unrelated chaotic system of the Lorenz type. Laboratory experiments illustrate the proposed linear methodology for effectively controlling chaos.
Directory of Open Access Journals (Sweden)
Linlin Gao
2015-11-01
Full Text Available From the perspective of vehicle dynamics, the four-wheel independent steering vehicle dynamics stability control method is studied, and a four-wheel independent steering varying parameter linear quadratic regulator control system is proposed with the help of expert control method. In the article, a four-wheel independent steering linear quadratic regulator controller for model following purpose is designed first. Then, by analyzing the four-wheel independent steering vehicle dynamic characteristics and the influence of linear quadratic regulator control parameters on control performance, a linear quadratic regulator control parameter adjustment strategy based on vehicle steering state is proposed to achieve the adaptive adjustment of linear quadratic regulator control parameters. In addition, to further improve the control performance, the proposed varying parameter linear quadratic regulator control system is optimized by genetic algorithm. Finally, simulation studies have been conducted by applying the proposed control system to the 8-degree-of-freedom four-wheel independent steering vehicle dynamics model. The simulation results indicate that the proposed control system has better performance and robustness and can effectively improve the stability and steering safety of the four-wheel independent steering vehicle.
van Ijsseldijk, E A; Valstar, E R; Stoel, B C; Nelissen, R G H H; Reiber, J H C; Kaptein, B L
2011-10-13
Accurate in vivo measurements methods of wear in total knee arthroplasty are required for a timely detection of excessive wear and to assess new implant designs. Component separation measurements based on model-based Roentgen stereophotogrammetric analysis (RSA), in which 3-dimensional reconstruction methods are used, have shown promising results, yet the robustness of these measurements is unknown. In this study, the accuracy and robustness of this measurement for clinical usage was assessed. The validation experiments were conducted in an RSA setup with a phantom setup of a knee in a vertical orientation. 72 RSA images were created using different variables for knee orientations, two prosthesis types (fixed-bearing Duracon knee and fixed-bearing Triathlon knee) and accuracies of the reconstruction models. The measurement error was determined for absolute and relative measurements and the effect of knee positioning and true seperation distance was determined. The measurement method overestimated the separation distance with 0.1mm on average. The precision of the method was 0.10mm (2*SD) for the Duracon prosthesis and 0.20mm for the Triathlon prosthesis. A slight difference in error was found between the measurements with 0° and 10° anterior tilt. (difference=0.08mm, p=0.04). The accuracy of 0.1mm and precision of 0.2mm can be achieved for linear wear measurements based on model-based RSA, which is more than adequate for clinical applications. The measurement is robust in clinical settings. Although anterior tilt seems to influence the measurement, the size of this influence is low and clinically irrelevant. Copyright © 2011 Elsevier Ltd. All rights reserved.
Kun, David William
Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external
A Multi-TeV Linear Collider Based on CLIC Technology : CLIC Conceptual Design Report
Energy Technology Data Exchange (ETDEWEB)
Aicheler, M [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Burrows, P. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Draper, M. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Garvey, T. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Lebrun, P. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Peach, K. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Phinney, N. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Schmickler, H. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Schulte, D. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Toge, N. [European Organization for Nuclear Research (CERN), Geneva (Switzerland)
2014-02-13
This report describes the accelerator studies for a future multi-TeV e^{+}e^{-} collider based on the Compact Linear Collider (CLIC) technology. The CLIC concept as described in the report is based on high gradient normal-conducting accelerating structures where the RF power for the acceleration of the colliding beams is extracted from a high-current Drive Beam that runs parallel with the main linac. The focus of CLIC R&D over the last years has been on addressing a set of key feasibility issues that are essential for proving the fundamental validity of the CLIC concept. The status of these feasibility studies are described and summarized. The report also includes a technical description of the accelerator components and R&D to develop the most important parts and methods, as well as a description of the civil engineering and technical services associated with the installation. Several larger system tests have been performed to validate the two-beam scheme, and of particular importance are the results from the CLIC test facility at CERN (CTF3). Both the machine and detector/physics studies for CLIC have primarily focused on the 3 TeV implementation of CLIC as a benchmark for the CLIC feasibility. This report also includes specific studies for an initial 500 GeV machine, and some discussion of possible intermediate energy stages. The performance and operation issues related to operation at reduced energy compared to the nominal, and considerations of a staged construction program are included in the final part of the report. The CLIC accelerator study is organized as an international collaboration with 43 partners in 22 countries. An associated report describes the physics potential and experiments at CLIC and a shorter report in preparation will focus on the CLIC implementation strategy, together with a plan for the CLIC R&D studies 2012–2016. Critical and important implementation issues such as cost, power and schedule will be addressed there.
A coalition formation game for transmitter cooperation in OFDMA uplink communications
Chelli, Ali
2014-12-01
The SC-FDMA (single-carrier frequency division multiple access) is the access scheme that has been adopted by 3GPP (3rd generation partnership project) for the LTE (long term evolution) uplink. The SC-FDMA is an attractive alternative to OFDMA (orthogonal frequency-division multiple access) especially on the uplink owing to its low peak-to-average power ratio. This fact increases the power efficiency and reduces the cost of the power amplifiers at the mobile terminals. The use of SC-FDMA on the uplink implies that for highly loaded cells the base station allocates a single subcarrier to each user. This results in the limitation of the achievable rate on the uplink. In this work, we propose a coalition game between mobile terminals that allows them to improve their performance by sharing their subcarriers without creating any interference to each other. The proposed scheme allows a fair use of the subcarriers and leads to a significant capacity gain for each user. The cooperation between the nodes is modelled using coalitional game theory. In this game, each coalition tries to maximize its utility in terms of rate. In the absence of cooperation cost, it can be shown that the grand coalition is sum-rate optimal and stable, i.e., the mobile terminals have no incentive to leave the grand coalition.
DSP-based Mitigation of RF Front-end Non-linearity in Cognitive Wideband Receivers
Grimm, Michael; Sharma, Rajesh K.; Hein, Matthias A.; Thomä, Reiner S.
2012-09-01
Software defined radios are increasingly used in modern communication systems, especially in cognitive radio. Since this technology has been commercially available, more and more practical deployments are emerging and its challenges and realistic limitations are being revealed. One of the main problems is the RF performance of the front-end over a wide bandwidth. This paper presents an analysis and mitigation of RF impairments in wideband front-ends for software defined radios, focussing on non-linear distortions in the receiver. We discuss the effects of non-linear distortions upon spectrum sensing in cognitive radio and analyse the performance of a typical wideband software-defined receiver. Digital signal processing techniques are used to alleviate non-linear distortions in the baseband signal. A feed-forward mitigation algorithm with an adaptive filter is implemented and applied to real measurement data. The results obtained show that distortions can be suppressed significantly and thus increasing the reliability of spectrum sensing.
Han, Xiaobao; Li, Huacong; Jia, Qiusheng
2017-12-01
For dynamic decoupling of polynomial linear parameter varying(PLPV) system, a robust dominance pre-compensator design method is given. The parameterized precompensator design problem is converted into an optimal problem constrained with parameterized linear matrix inequalities(PLMI) by using the conception of parameterized Lyapunov function(PLF). To solve the PLMI constrained optimal problem, the precompensator design problem is reduced into a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a new constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator is achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation on a turbofan engine PLPV model.
Analysis of Relativity Premium in Bonus-Malus System Based on Optimal Linear Method
Directory of Open Access Journals (Sweden)
Yu Chen
2014-01-01
Full Text Available A bonus-malus system plays a very important role in actuarial mathematics through determining its relativity premium, which is extensively used in automobile insurance. There are many ways including Bayesian estimator and ordinary linear estimator to calculate the relativity premium. There is no doubt that Bayesian estimator is the most accurate estimator; however, it is undesirable for commercial purposes for its rather irregular pattern. This paper aims to introduce an optimal linear estimator for relativity premium, which has a simple pattern and is obtained under the quadratic loss function such that the result is close to Bayesian method. The Loimaranta efficiency of such an optimal linear estimator has been studied and compared with the two methods mentioned above.
Field-based observations confirm linear scaling of sand flux with wind stress
Martin, Raleigh L
2016-01-01
Wind-driven sand transport generates atmospheric dust, forms dunes, and sculpts landscapes. However, it remains unclear how the sand flux scales with wind speed, largely because models do not agree on how particle speed changes with wind shear velocity. Here, we present comprehensive measurements from three new field sites and three published studies, showing that characteristic saltation layer heights, and thus particle speeds, remain approximately constant with shear velocity. This result implies a linear dependence of saltation flux on wind shear stress, which contrasts with the nonlinear 3/2 scaling used in most aeolian process predictions. We confirm the linear flux law with direct measurements of the stress-flux relationship occurring at each site. Models for dust generation, dune migration, and other processes driven by wind-blown sand on Earth, Mars, and several other planetary surfaces should be modified to account for linear stress-flux scaling.
Linear Look-ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation
Directory of Open Access Journals (Sweden)
John L Kubie
2012-04-01
Full Text Available The crisp organization of the firing bumps of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed linear look-ahead, by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies of rigid modules of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-minute walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive-cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: The pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look ahead starting in any location and extending in any direction. We speculate that this process may: 1. compute linear paths to goals; 2. update grid cell firing during navigation; and 3. stabilize the rigid modules of grid cells and conjunctive cells.
A technique based on pulse shape comparison for linearizing compressed signals
Cattaneo, P W
2002-01-01
A nuclear electronics system designed to perform high precision energy measurement on a large dynamic range through high speed sampling of the output might be impossible to match to an adequate ADC. A solution consists in compressing the signal before digitization and linearizing it after with a look-up table, encoding the inverse of the compression function. This look-up table can be constructed using test pulses, the smallest of which is in the linear part and the largest spans the whole dynamic range. Reconstructing these pulse shapes and requiring them to be omothetic generates the look-up table providing a minimal distortion in the RMS sense.
[Stellar spectrum parameter measurement based on line index by linear regression].
Tan, Xin; Pan, Jing-Chang; Wang, Jie; Luo, A-Li; Tu, Liang-Ping
2013-05-01
Using the Lick line index, according to the magnanimity characteristics of the spectrum an efficient algorithm of the atmospheric physical parameters measurement by the linear regression method from the point of view of statistical regression was designed. The linear regression was used to achieve the best regression effect by selecting the type of regression and the composition of line index. The formula obtained from the regression model makes the computation speed fast when applied to new data, and the clarity and ease of analysis processing can not be reached by other methods. The experimental results show that through the line index regression method to get the atmospheric physical parameters is feasible.
Wang, Chen; Xie, G.; Wang, L.; Cao, M.
The aim of the present study is to investigate the locomotion control of a robotic fish. To achieve this goal, we design a control architecture based on a novel central pattern generator (CPG) and implement it as a system of coupled linear oscillators. This design differs significantly from the
Wang, Yong; Wu, Qiao-Feng; Chen, Chen; Wu, Ling-Yun; Yan, Xian-Zhong; Yu, Shu-Guang; Zhang, Xiang-Sun; Liang, Fan-Rong
2012-01-01
Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. Our result demonstrates that metabolic profiling might be a promising method to
An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.
Tian, Zhen; Li, Yongbao; Folkerts, Michael; Shi, Feng; Jiang, Steve B; Jia, Xun
2015-10-21
Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum
Ferwerda, H.A.; Hoenders, B.J.; Slump, C.H.
The fully relativistic quantum mechanical treatment of paraxial electron-optical image formation initiated in the previous paper (this issue) is worked out and leads to a rigorous foundation of the linear transfer theory. Moreover, the status of the relativistic scaling laws for mass and wavelength,
DEFF Research Database (Denmark)
Shabbir, Aamir; Javakhishvili, Irakli; Cerveny, Silvina
2016-01-01
Supramolecular polymers possess versatile mechanical properties and a unique ability to respond to external stimuli. Understanding the rich dynamics of such associative polymers is essential for tailoring user-defined properties in many products. Linear copolymers of 2-methoxyethyl acrylate (MEA)...
A Hierarchical Linear Model for Estimating Gender-Based Earnings Differentials.
Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey
1998-01-01
Estimates of gender earnings inequality in data from 116,431 Jewish workers were compared using a hierarchical linear model (HLM) and ordinary least squares model. The HLM allows estimation of the extent to which earnings inequality depends on occupational characteristics. (SK)
Directory of Open Access Journals (Sweden)
Sankar Prasad Mondal
2013-11-01
Full Text Available In this paper the First Order Linear Fuzzy Ordinary Differential Equations are described. Here coefficients and /or initial condition of said differential equation are taken as the Generalized Triangular Fuzzy Numbers (GTFNs.The solution procedure of this Fuzzy Differential Equation is developed by Lagrange Multiplier Method. An imprecise barometric pressure problem is described.
Robust observer-based fault estimation and accommodation of discrete-time piecewise linear systems
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba; Bak, Thomas
2013-01-01
are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example....
A Practical Approach to Inquiry-Based Learning in Linear Algebra
Chang, J.-M.
2011-01-01
Linear algebra has become one of the most useful fields of mathematics since last decade, yet students still have trouble seeing the connection between some of the abstract concepts and real-world applications. In this article, we propose the use of thought-provoking questions in lesson designs to allow two-way communications between instructors…
Student Reactions to Learning Theory Based Curriculum Materials in Linear Algebra--A Survey Analysis
Cooley, Laurel; Vidakovic, Draga; Martin, William O.; Dexter, Scott; Suzuki, Jeff
2016-01-01
In this report we examine students' perceptions of the implementation of carefully designed curriculum materials (called modules) in linear algebra courses at three different universities. The curricular materials were produced collaboratively by STEM and mathematics education faculty as members of a professional learning community (PLC) over…
LMI-based gain scheduled controller synthesis for a class of linear parameter varying systems
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Anderson, Brian; Lanzon, Alexander
2006-01-01
This paper presents a novel method for constructing controllers for a class of single-input multiple-output (SIMO) linear parameter varying (LPV) systems. This class of systems encompasses many physical systems, in particular systems where individual components vary with time, and is therefore...
A novel method of drift-scanning stars suppression based on the standardized linear filter
Lin, Jianlin; Ping, Xijian; Hou, Guanghua; Ma, Debao
2011-11-01
A large number of stars in the drift-scanning star image have interfered with the detection of small target, this paper proposes an adaptive linear filtering method to achieve the small target detection by suppressing the stars. Firstly, the characteristics of stars, interest target and noise three different representative objects in the star image are analyzed, then the standardized linear filter is constructed to suppress the stars. For the purpose of decreasing the influence region of stars filtering uniformly, a gradient linear filter is constructed to modify the stars suppression method with the standardized linear filter. Then the filter parameter selection method is given. Finally, a multi-frame target track experiment on the real drift-scanning data is made to testify the validity of the proposed method. With the processing results of different methods, it has been showed that the proposed method for suppressing stars with different length and lean angle has a better effect, higher robustness and easier application than the others.
Linear SVM-Based Android Malware Detection for Reliable IoT Services
National Research Council Canada - National Science Library
Hyo-Sik Ham; Hwan-Hee Kim; Myung-Sup Kim; Mi-Jung Choi
2014-01-01
.... In this paper, we apply a linear support vector machine (SVM) to detect Android malware and compare the malware detection performance of SVM with that of other machine learning classifiers. Through experimental validation, we show that the SVM outperforms other machine learning classifiers.
DEFF Research Database (Denmark)
Skjøth-Rasmussen, Jane; Roed, Henrik; Ohlhues, Lars
2010-01-01
Primarily, gamma knife centers are predominant in publishing results on arteriovenous malformations (AVM) treatments including reports on risk profile. However, many patients are treated using a linear accelerator-most of these at smaller centers. Because this setting is different from a large...
Kler, A. M.; Maximov, A. S.; Epishkin, N. O.
2017-09-01
The paper describes the developed method for analyzing technological schemes of thermal power plants based on solving problems of auxiliary linear programming. This method involves solving the linear programming problems to evaluate the effect of supply and removal of heat or material flows of various sizes at different points of the technological scheme of a thermal power plant (TPP). The method effectiveness is demonstrated by the example of the coaldust steam turbine unit with nominal electrical output of 660 MW. As a result of its application, the change of the technological scheme of the unit was found to provide reduction in electricity cost by 0.3%.
Ewen, Hamish Maclean; Riccardo, Bartolini
The non-linear beam dynamics of a circular accelerator, such as the Large Hadron Collider, can have a significant impact on its operation. In order to avoid limitations on the performance reach of the accelerator, and ensure machine protection, it is vital that the beam dynamics are well understood and controlled. This thesis presents the results of studies of non-linear beam dynamics undertaken on the Large Hadron Collider at CERN, during the 2010 to 2013 period. It sets out to quantify the understanding of the non-linear beam dynamics through the comparison of beam-based measurements to simulation, and where able and appropriate seeks to explain deviations of measurement from the model, and define corrections for relevant aspects of the dynamics. The analyses presented in this thesis represent considerable advances in the understanding of the LHC beam dynamics which should allow for an improved operation of the machine in the coming years.
DEFF Research Database (Denmark)
Cimoli, Bruno; Johansen, Tom Keinicke; Olmos, Juan Jose Vegas
2018-01-01
We report a high performance linear phase low pass filter (LPF) designed for partial response (PR) modulations. For the implementation, we adopted microstrip technology and a variant of the standard stepped‐impedance technique. Defected ground structures (DGS) are used for increasing the characte......We report a high performance linear phase low pass filter (LPF) designed for partial response (PR) modulations. For the implementation, we adopted microstrip technology and a variant of the standard stepped‐impedance technique. Defected ground structures (DGS) are used for increasing...... the characteristic impedance of transmission lines. Experimental results prove that the proposed filter can successfully modulate a non‐return‐to‐zero (NRZ) signal into a five levels PR one....
Induction Motor Drive System Based on Linear Active Disturbance Rejection Controller
Liu, Liying; Zhang, Yongli; Yao, Qingmei
It is difficult to establish an exact mathematical model for the induction motor and the robustness is poor of the vector control system using PI regulator. This paper adopts the linear active disturbance rejection controller (LADRC) to control inductor motor. LADRC doesn't need the exact mathematical model of motor and it can not only estimate but also compensate the general disturbance that includes the coupling items in model of motor and parameters perturbations by linear extended state observer (LESO), so the rotor flux and torque fully decouple. As a result, the performance is improved. To prove the above control scheme, the proposed control system has been simulated in MATLAB/SIMULINK, and the comparison was made with PID. Simulation results show that LADRC' has better performance and robustness than PID.
Inverse estimation of multiple muscle activations based on linear logistic regression.
Sekiya, Masashi; Tsuji, Toshiaki
2017-07-01
This study deals with a technology to estimate the muscle activity from the movement data using a statistical model. A linear regression (LR) model and artificial neural networks (ANN) have been known as statistical models for such use. Although ANN has a high estimation capability, it is often in the clinical application that the lack of data amount leads to performance deterioration. On the other hand, the LR model has a limitation in generalization performance. We therefore propose a muscle activity estimation method to improve the generalization performance through the use of linear logistic regression model. The proposed method was compared with the LR model and ANN in the verification experiment with 7 participants. As a result, the proposed method showed better generalization performance than the conventional methods in various tasks.
Endo, Vitor Takashi; de Carvalho Pereira, José Carlos
2017-05-01
Material properties description and understanding are essential aspects when computational solid mechanics is applied to product development. In order to promote injected fiber reinforced thermoplastic materials for structural applications, it is very relevant to develop material characterization procedures, considering mechanical properties variation in terms of fiber orientation and loading time. Therefore, a methodology considering sample manufacturing, mechanical tests and data treatment is described in this study. The mathematical representation of the material properties was solved by a linear viscoelastic constitutive model described by Prony series, which was properly adapted to orthotropic materials. Due to the large number of proposed constitutive model coefficients, a parameter identification method was employed to define mathematical functions. This procedure promoted good correlation among experimental tests, and analytical and numerical creep models. Such results encourage the use of numerical simulations for the development of structural components with the proposed linear viscoelastic orthotropic constitutive model. A case study was presented to illustrate an industrial application of proposed methodology.
A Low-Complexity ESPRIT-Based DOA Estimation Method for Co-Prime Linear Arrays.
Sun, Fenggang; Gao, Bin; Chen, Lizhen; Lan, Peng
2016-08-25
The problem of direction-of-arrival (DOA) estimation is investigated for co-prime array, where the co-prime array consists of two uniform sparse linear subarrays with extended inter-element spacing. For each sparse subarray, true DOAs are mapped into several equivalent angles impinging on the traditional uniform linear array with half-wavelength spacing. Then, by applying the estimation of signal parameters via rotational invariance technique (ESPRIT), the equivalent DOAs are estimated, and the candidate DOAs are recovered according to the relationship among equivalent and true DOAs. Finally, the true DOAs are estimated by combining the results of the two subarrays. The proposed method achieves a better complexity-performance tradeoff as compared to other existing methods.
Kinematics Modeling and Simulation of a Bionic Fish Tail System Based on Linear Hypocycloid
Directory of Open Access Journals (Sweden)
Shu-yan Wang
2015-01-01
Full Text Available Kinematics and simulation study on a two-joint linear hypocycloid tail driving system composed of a special planetary gear system and a linkage mechanism are conducted in this paper. First, the composition and working principle of the linear hypocycloid tail transmission system are introduced and analyzed. Second, the kinematics study on the transmission mechanism is conducted with graphical method of vector equation. The relationships between the caudal peduncle stroke, the tail fin swing angle, and the phase difference with structure parameters are studied, and further optimization of structure sizes (i.e., linkage length, sun gear’s diameter, the intersection angle between planet gears, etc. is developed. At last, simulation and comparative study on a biofish in sample parameters with a live fish of Carp is conducted in MATLAB. The study would serve for underwater vehicles thruster design and its mechanism.
Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun
2015-01-01
The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Skjøth-Rasmussen, Jane; Roed, Henrik; Ohlhues, Lars
2010-01-01
Primarily, gamma knife centers are predominant in publishing results on arteriovenous malformations (AVM) treatments including reports on risk profile. However, many patients are treated using a linear accelerator-most of these at smaller centers. Because this setting is different from a large...... gamma knife center, the risk profile at Linac departments could be different from the reported experience. Prescribed radiation doses are dependent on AVM volume. This study details results from a medium sized Linac department center focusing on risk profiles....
OPTIMAL AIRCRAFT CONTROL SYNTHESIS BASED ON THE EQUATIONS OF NON-LINEAR DYNAMICS
Directory of Open Access Journals (Sweden)
Viktor F. Dil
2017-01-01
Full Text Available The article considers the technique of the synthesis of non-linear aircraft control systems by flight optimization us- ing inverse dynamics problems. To synthesize control algorithms a non-linear model of aircraft flight and trajectory movement is used. The authors define method stages of flying level synthesis which include: selection of aircraft reference movements in accordance with three degrees of freedom, structuring the control algorithms and their parameters, defining the proximity of current and reference movements by means of a quadratic functional and further extremum-minimum movement organization by the gradient method. Through the optimized parameters of flying level the direct dynamics problem of trajectory level control of the aircraft spatial movement is solved. The basis for calculating the aircraft trajecto- ry parameters is a non-linear model of the trajectory movement for which flying level output parameters serve as input data. The trajectory level output parameters are defined by numerical integration of input signals considering aircraft dynamic blow coefficients. The structure diagram of aircraft spatial movement control organization is developed. The flight contour functioning is examined using numerical modeling in MathCad and Paskal programs. Reference parameters were deter- mined by Paskal simulation modeling according to the reaction of a non-linear aircraft model to the “bounces” of aerody- namical flight controls. It is shown that the spatial control problem is optimal in terms of input control realization. Besides, in comparison with [9] it is possible to state that due to energy reversibility of rotational and progressive movements only the content of direct and inversed problems of dynamics changes.
2014-09-20
of the automata -theoretic approach,” in Formal Methods for Real-Time and Probabilistic Systems, ser. Lecture Notes in Computer Science, 1999, vol...1601, pp. 265–276. [11] J. Klein and C. Baier, “Experiments with deterministic ω- automata for formulas of linear temporal logic,” in Implementation and...Application of Automata . Springer, 2004. [12] S. Safra, “On the complexity of ω- automata ,” in Proceedings of the 29th Annual Symposium on Foundations
OPTIMAL LINEAR COMBINED FILTERING OF RANDOM SEQUENCES BASED ON THE RECURSIVE LEAST SQUARES METHOD
Directory of Open Access Journals (Sweden)
V. M. Artemiev
2015-01-01
Full Text Available The problem of the synthesis of linear combined filter for the criterion of minimizing current losses on the basis of the recursive least squares method is being solved. This approach does not requirea priori knowledge of the statistical characteristics of impacts that is an advantage compared with the Kalman filter. A comparative evaluation of the filters’ accuracy is provided using the values of variances of the filtering errors.
Energy Technology Data Exchange (ETDEWEB)
Brau, James E [Univ. of Oregon
2013-04-22
The U.S Linear Collider Detector R&D program, supported by the DOE and NSF umbrella grants to the University of Oregon, made significant advances on many critical aspects of the ILC detector program. Progress advanced on vertex detector sensor development, silicon and TPC tracking, calorimetry on candidate technologies, and muon detection, as well as on beamline measurements of luminosity, energy, and polarization.
Grosse Frie, Kirstin; Janssen, Christian
2009-01-01
Based on the theoretical and empirical approach of Pierre Bourdieu, a multivariate non-linear method is introduced as an alternative way to analyse the complex relationships between social determinants and health. The analysis is based on face-to-face interviews with 695 randomly selected respondents aged 30 to 59. Variables regarding socio-economic status, life circumstances, lifestyles, health-related behaviour and health were chosen for the analysis. In order to determine whether the respondents can be differentiated and described based on these variables, a non-linear canonical correlation analysis (OVERALS) was performed. The results can be described on three dimensions; Eigenvalues add up to the fit of 1.444, which can be interpreted as approximately 50 % of explained variance. The three-dimensional space illustrates correspondences between variables and provides a framework for interpretation based on latent dimensions, which can be described by age, education, income and gender. Using non-linear canonical correlation analysis, health characteristics can be analysed in conjunction with socio-economic conditions and lifestyles. Based on Bourdieus theoretical approach, the complex correlations between these variables can be more substantially interpreted and presented.
Gocke, Elmar; Müller, Lutz; Pfister, Thomas
2009-11-12
Prior to having performed in depth toxicological, genotoxicological and DMPK studies on ethyl methanesulfonate (EMS) providing solid evidence for a thresholded dose response relationship, we had prepared and shared with regulatory authorities a preliminary risk estimate based on standard linear dose-effect projections. We estimated that maximal lifetime cancer risk was in the order of 10(-3) (for lifetime ingestion of the maximally contaminated tablets) or 10(-4) for the exposure lasting for 3 months. This estimate was based on a lifetime cancer study with methyl methanesulfonate (MMS; as insufficient data were available for EMS) in rodents and default linear back extrapolation. Analogous estimates were made specifically for breast cancer based on short term tumorigenicity studies with EMS in rats, for the induction of heritable mutations based on specific locus and dominant lethal tests in mice and for the induction of birth defects based on teratogenicity studies in mice. We concluded that even under worst case assumptions of linear dose relations the chance of experiencing these adverse effects would be very small, comprising at most a minute additional burden among the background incidence of the patients.
Fernández-Durán, J J
2007-06-01
Johnson and Wehrly (1978, Journal of the American Statistical Association 73, 602-606) and Wehrly and Johnson (1980, Biometrika 67, 255-256) show one way to construct the joint distribution of a circular and a linear random variable, or the joint distribution of a pair of circular random variables from their marginal distributions and the density of a circular random variable, which in this article is referred to as joining circular density. To construct flexible models, it is necessary that the joining circular density be able to present multimodality and/or skewness in order to model different dependence patterns. Fernández-Durán (2004, Biometrics 60, 499-503) constructed circular distributions based on nonnegative trigonometric sums that can present multimodality and/or skewness. Furthermore, they can be conveniently used as a model for circular-linear or circular-circular joint distributions. In the current work, joint distributions for circular-linear and circular-circular data constructed from circular distributions based on nonnegative trigonometric sums are presented and applied to two data sets, one for circular-linear data related to the air pollution patterns in Mexico City and the other for circular-circular data related to the pair of dihedral angles between consecutive amino acids in a protein.
Zafar, Haroon; Breathnach, Aedán; Subhash, Hrebesh M; Leahy, Martin J
2015-05-01
Photoacoustic imaging (PAI) with a linear-array-based probe can provide a convenient means of imaging the human microcirculation within its native structural context and adds functional information. PAI using a multielement linear transducer array combined with multichannel collecting system was used for in vivo volumetric imaging of the blood microcirculation, the total concentration of hemoglobin (HbT), and the hemoglobin oxygen saturation (sO₂) within human tissue. Three-dimensional (3-D) PA and ultrasound (US) volumetric scans were acquired from the forearm skin by linearly translating the transducer with a stepper motor over a region of interest, while capturing two-dimensional images using 15, 21, and 40 MHz frequency transducer probes. For the microvasculature imaging, PA images were acquired at 800- and 1064-nm wavelengths. For the HbT and sO₂ estimates, PA images were collected at 750- and 850-nm wavelengths. 3-D microcirculation, HbT, and sO₂ maps of the forearm skin were obtained from normal subjects. The linear-array-based PAI has been found promising in terms of resolution, imaging depth, and imaging speed for in vivo microcirculation imaging within human skin. We believe that a reflection type probe, similar to existing clinical US probes, is most likely to succeed in real clinical applications. Its advantages include ease of use, speed, and familiarity for radiographers and clinicians.
DOA Finding with Support Vector Regression Based Forward-Backward Linear Prediction.
Pan, Jingjing; Wang, Yide; Le Bastard, Cédric; Wang, Tianzhen
2017-05-27
Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward-backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This paper proposes the combination of the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots, and signal-to-noise ratios (SNRs). Simulation results show the effectiveness of the proposed method.
DOA Finding with Support Vector Regression Based Forward–Backward Linear Prediction
Directory of Open Access Journals (Sweden)
Jingjing Pan
2017-05-01
Full Text Available Direction-of-arrival (DOA estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward–backward linear prediction (FBLP is able to directly deal with coherent signals. Support vector regression (SVR is robust with small samples. This paper proposes the combination of the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots, and signal-to-noise ratios (SNRs. Simulation results show the effectiveness of the proposed method.
DEFF Research Database (Denmark)
Aili, David; Hansen, Martin Kalmar; Renzaho, Richard Fulgence
2013-01-01
Polybenzimidazole is a highly hygroscopic polymer that can be doped with aqueous KOH to give a material with high ion conductivity in the 10−2Scm−1 range, which in combination with its low gas permeability makes it an interesting electrolyte material for alkaline water electrolysis. In this study...... on their linear counterpart. The technical feasibility of the membranes was evaluated by the preliminary water electrolysis tests showing performance comparable to that of commercially available cell separators with great potential of further improvement....
2014-01-01
Background Problem-based learning (PBL) is well established in medical education and beyond, and continues to be developed and explored. Challenges include how to connect the somewhat abstract nature of classroom-based PBL with clinical practice and how to maintain learner engagement in the process of PBL over time. Objective A study was conducted to investigate the efficacy of decision-PBL (D-PBL), a variant form of PBL that replaces linear PBL cases with virtual patients. These Web-based interactive cases provided learners with a series of patient management pathways. Learners were encouraged to consider and discuss courses of action, take their chosen management pathway, and experience the consequences of their decisions. A Web-based application was essential to allow scenarios to respond dynamically to learners’ decisions, to deliver the scenarios to multiple PBL classrooms in the same timeframe, and to record centrally the paths taken by the PBL groups. Methods A randomized controlled trial in crossover design was run involving all learners (N=81) in the second year of the graduate entry stream for the undergraduate medicine program at St George’s University of London. Learners were randomized to study groups; half engaged in a D-PBL activity whereas the other half had a traditional linear PBL activity on the same subject material. Groups alternated D-PBL and linear PBL over the semester. The measure was mean cohort performance on specific face-to-face exam questions at the end of the semester. Results D-PBL groups performed better than linear PBL groups on questions related to D-PBL with the difference being statistically significant for all questions. Differences between the exam performances of the 2 groups were not statistically significant for the questions not related to D-PBL. The effect sizes for D-PBL–related questions were large and positive (>0.6) except for 1 question that showed a medium positive effect size. The effect sizes for questions
Poulton, Terry; Ellaway, Rachel H; Round, Jonathan; Jivram, Trupti; Kavia, Sheetal; Hilton, Sean
2014-11-05
Problem-based learning (PBL) is well established in medical education and beyond, and continues to be developed and explored. Challenges include how to connect the somewhat abstract nature of classroom-based PBL with clinical practice and how to maintain learner engagement in the process of PBL over time. A study was conducted to investigate the efficacy of decision-PBL (D-PBL), a variant form of PBL that replaces linear PBL cases with virtual patients. These Web-based interactive cases provided learners with a series of patient management pathways. Learners were encouraged to consider and discuss courses of action, take their chosen management pathway, and experience the consequences of their decisions. A Web-based application was essential to allow scenarios to respond dynamically to learners' decisions, to deliver the scenarios to multiple PBL classrooms in the same timeframe, and to record centrally the paths taken by the PBL groups. A randomized controlled trial in crossover design was run involving all learners (N=81) in the second year of the graduate entry stream for the undergraduate medicine program at St George's University of London. Learners were randomized to study groups; half engaged in a D-PBL activity whereas the other half had a traditional linear PBL activity on the same subject material. Groups alternated D-PBL and linear PBL over the semester. The measure was mean cohort performance on specific face-to-face exam questions at the end of the semester. D-PBL groups performed better than linear PBL groups on questions related to D-PBL with the difference being statistically significant for all questions. Differences between the exam performances of the 2 groups were not statistically significant for the questions not related to D-PBL. The effect sizes for D-PBL-related questions were large and positive (>0.6) except for 1 question that showed a medium positive effect size. The effect sizes for questions not related to D-PBL were all small (≤0
Dattoli, Giuseppe
2005-01-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. A code devoted to the analysis of this type of problems should be fast and reliable: conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problem in accelerators. The extension of these method to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators implemented numerically in C++. We show that the integration procedure is capable of reproducing the onset of an instability and effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, parametric studies a...
2-μm numerical analysis of linear-cavity FP structures based on fiber Bragg gratings
Bai, Zhuoya; Yan, Fengping; Zhang, Luna; Bai, Yan; Liu, Shuo; Zhou, Hong; Hou, Yafei; Zhang, Ning
2017-05-01
The linewidth performance of all-fiber, linear-cavity Fabry-Perot structures based on fiber Bragg gratings operating at 2-μm band has been investigated numerically. The output linewidth performance of two symmetrical and asymmetrical cavities has been theoretically studied and comprehensively compared. The numerical analysis is based on the transmission matrix method with the simplified parameters. The simulation results show that cavity lengths, cavity lengths ratio, grating lengths, grating lengths ratio, as well as index modulation depths, affect the output linewidth performance. The tolerance ability of the asymmetrical structure is first proposed and investigated under 1 mm accuracy, and single-frequency output can be realized by properly adjusting the properties of the proposed composite linear cavity structure.
Energy Technology Data Exchange (ETDEWEB)
Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)
1996-05-01
In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.
Linear regression-based efficient SVM learning for large-scale classification.
Wu, Jianxin; Yang, Hao
2015-10-01
For large-scale classification tasks, especially in the classification of images, additive kernels have shown a state-of-the-art accuracy. However, even with the recent development of fast algorithms, learning speed and the ability to handle large-scale tasks are still open problems. This paper proposes algorithms for large-scale support vector machines (SVM) classification and other tasks using additive kernels. First, a linear regression SVM framework for general nonlinear kernel is proposed using linear regression to approximate gradient computations in the learning process. Second, we propose a power mean SVM (PmSVM) algorithm for all additive kernels using nonsymmetric explanatory variable functions. This nonsymmetric kernel approximation has advantages over the existing methods: 1) it does not require closed-form Fourier transforms and 2) it does not require extra training for the approximation either. Compared on benchmark large-scale classification data sets with millions of examples or millions of dense feature dimensions, PmSVM has achieved the highest learning speed and highest accuracy among recent algorithms in most cases.
Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa
2008-01-01
This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.
Study on sampling of continuous linear system based on generalized Fourier transform
Li, Huiguang
2003-09-01
In the research of signal and system, the signal's spectrum and the system's frequency characteristic can be discussed through Fourier Transform (FT) and Laplace Transform (LT). However, some singular signals such as impulse function and signum signal don't satisfy Riemann integration and Lebesgue integration. They are called generalized functions in Maths. This paper will introduce a new definition -- Generalized Fourier Transform (GFT) and will discuss generalized function, Fourier Transform and Laplace Transform under a unified frame. When the continuous linear system is sampled, this paper will propose a new method to judge whether the spectrum will overlap after generalized Fourier transform (GFT). Causal and non-causal systems are studied, and sampling method to maintain system's dynamic performance is presented. The results can be used on ordinary sampling and non-Nyquist sampling. The results also have practical meaning on research of "discretization of continuous linear system" and "non-Nyquist sampling of signal and system." Particularly, condition for ensuring controllability and observability of MIMO continuous systems in references 13 and 14 is just an applicable example of this paper.
Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang
2018-01-01
Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.
Aneesh, R; Khijwania, Sunil K
2012-04-20
An optical fiber humidity sensor employing an in-house scaled TiO2-nanoparticle doped nanostructured thin film as the fiber sensing cladding and evanescent wave absorption is reported. The main objective of the present work is to achieve a throughout-linear sensor response with high sensitivity, possibly over a wide dynamic range using the simplest possible sensor geometry. In order to realize this, first, the nanostructured sensing film is synthesized over a short length of a centrally decladded straight and uniform optical fiber and then a comprehensive experimental investigation is carried out to optimize the design configuration/parameters of the nanostructured sensing film and to achieve the best possible sensor response. Much improved sensitivity of 27.1 mV/%RH is observed for the optimized sensor along with a throughout-linear sensor response over a dynamic range as wide as 24% to 95%RH with an average response time of 0.01 s for humidification and 0.06 s for desiccation. In addition, the sensor exhibits a very good degree of reversibility and repeatability.
Active learning for semi-supervised clustering based on locally linear propagation reconstruction.
Chang, Chin-Chun; Lin, Po-Yi
2015-03-01
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.
Passive impedance-based second-order sliding mode control for non-linear teleoperators
Directory of Open Access Journals (Sweden)
Luis G García-Valdovinos
2017-02-01
Full Text Available Bilateral teleoperation systems have attracted significant attention in the last decade mainly because of technological advancements in both the communication channel and computers performance. In addition, non-linear multi-degree-of-freedom bilateral teleoperators along with state observers have become an open research area. In this article, a model-free exact differentiator is used to estimate the full state along with a chattering-free second-order sliding mode controller to guarantee a robust impedance tracking under both constant and an unknown time delay of non-linear multi-degree-of-freedom robots. The robustness of the proposed controller is improved by introducing a change of coordinates in terms of a new nominal reference similar to that used in adaptive control theory. Experimental results that validate the predicted behaviour are presented and discussed using a Phantom Premium 1.0 as the master robot and a Catalyst-5 virtual model as the slave robot. The dynamics of the Catalyst-5 system is solved online.
Design of Attitude Control System for UAV Based on Feedback Linearization and Adaptive Control
Directory of Open Access Journals (Sweden)
Wenya Zhou
2014-01-01
Full Text Available Attitude dynamic model of unmanned aerial vehicles (UAVs is multi-input multioutput (MIMO, strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range, and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.
Ptaszek, Paweł; Żmudziński, Daniel; KRUK, Joanna; Kaczmarczyk, Kacper; Rożnowski, Wojciech; Berski, Wiktor
2013-01-01
The aim of this work was to evaluate the physicochemical properties of fresh foams based on egg white proteins, xanthan gum and gum Arabic. The distributions of the size of gas bubbles suspended in liquid were determined, as well as density and volume fraction of gas phase of the generated foams. Additionally, the viscoelastic properties in the linear range were measured, and the results were analyzed with the use of the fractional Zener model. It was shown, that foam supplementation with hyd...
Tan, Xinran; Zhu, Fan; Wang, Chao; Shi, Jian; Qi, Xue; Yu, Yang; Yuan, Feng; Tan, Jiubin
2017-11-01
This paper presents a capacitive sensor-based micro-angle measurement (CSMAM) method that uses an angular-to-linear displacement conversion to achieve high accuracy. The principal and secondary error components of CSMAMs are modeled and analyzed to reveal their impacts on the measurement accuracy. The theoretical accuracies of six types of commonly used CSMAMs are analyzed to determine the optimum configuration of capacitive sensors for 1D and 2D micro-angle measurements. An angular-to-linear displacement conversion method with a linear motional stage and a hemisphere decoupler is used to eliminate the principal error of CSMAM. Experimental results indicate that the optimized CSMAM can achieve accuracies of 0.157 arc sec and 0.052 arc sec in the ranges of ±900 arc sec and ±300 arc sec, respectively, in the case that the effective length of the rotation arm is 100 mm and the linear displacement measurement accuracy of the capacitive sensor is 2 nm. These results can be used as a reference to further improve CSMAM designs and achieve high accuracy in a large measurement range, for use in a wide range of precision engineering applications including angle metrology, micro- and nano-radian angle generators, beam steering mechanisms, and high-performance precision stages.
Tan, Xinran; Zhu, Fan; Wang, Chao; Shi, Jian; Qi, Xue; Yu, Yang; Yuan, Feng; Tan, Jiubin
2017-11-01
This paper presents a capacitive sensor-based micro-angle measurement (CSMAM) method that uses an angular-to-linear displacement conversion to achieve high accuracy. The principal and secondary error components of CSMAMs are modeled and analyzed to reveal their impacts on the measurement accuracy. The theoretical accuracies of six types of commonly used CSMAMs are analyzed to determine the optimum configuration of capacitive sensors for 1D and 2D micro-angle measurements. An angular-to-linear displacement conversion method with a linear motional stage and a hemisphere decoupler is used to eliminate the principal error of CSMAM. Experimental results indicate that the optimized CSMAM can achieve accuracies of 0.157 arc sec and 0.052 arc sec in the ranges of ±900 arc sec and ±300 arc sec, respectively, in the case that the effective length of the rotation arm is 100 mm and the linear displacement measurement accuracy of the capacitive sensor is 2 nm. These results can be used as a reference to further improve CSMAM designs and achieve high accuracy in a large measurement range, for use in a wide range of precision engineering applications including angle metrology, micro- and nano-radian angle generators, beam steering mechanisms, and high-performance precision stages.
Biped Robot Gait Planning Based on 3D Linear Inverted Pendulum Model
Yu, Guochen; Zhang, Jiapeng; Bo, Wu
2018-01-01
In order to optimize the biped robot’s gait, the biped robot’s walking motion is simplify to the 3D linear inverted pendulum motion mode. The Center of Mass (CoM) locus is determined from the relationship between CoM and the Zero Moment Point (ZMP) locus. The ZMP locus is planned in advance. Then, the forward gait and lateral gait are simplified as connecting rod structure. Swing leg trajectory using B-spline interpolation. And the stability of the walking process is discussed in conjunction with the ZMP equation. Finally the system simulation is carried out under the given conditions to verify the validity of the proposed planning method.
Energy Technology Data Exchange (ETDEWEB)
Li Guoyu; Li Yan [Institute of Information Engineering, Handan College, Handan, 056005 (China); Zhao Peng, E-mail: guoyu_li@yahoo.cn [School of Physics and Optoelectronic Engineering, Dalian University of Technology, Dalian 116024 (China)
2011-02-01
In optical frequency domain reflectometry (OFDR) system, the spatial resolution is obtained by using the total frequency-sweep span of the tunable laser. However, in practice, the spatial resolution is severely limited by nonlinearity in the lightwave-frequency sweep of the tunable laser. A closed-loop PZT modulated DBR linear fiber laser is proposed to improve the spatial resolution of the OFDR system. Experimental results show that the spatial resolution of OFDR system has improved greatly. When the frequency sweep excursion is 66GHz and the fiber under test (FUT) is 7 m, the OFDR system has a spatial resolution of 1.5 m with open-loop PZT modulated laser. But the spatial resolution increases to 35 cm with closed-loop PZT modulated laser.
Wind turbine fatigue damage evaluation based on a linear model and a spectral method
DEFF Research Database (Denmark)
Tibaldi, Carlo; Henriksen, Lars Christian; Hansen, Morten Hartvig
2015-01-01
presents a method to estimate wind turbine fatigue damage suited for optimization design applications. The method utilizes a high-order linear wind turbine model. The model comprehends a detailed description of the wind turbine and the controller. The fatigue is computed with a spectral method applied......Wind turbine multidisciplinary design optimization is currently the focus of several investigations because it has showed potential in reducing the cost of energy. This design approach requires fast methods to evaluate wind turbine loads with a sufficiently high level of fidelity. This paper...... to power spectral densities of wind turbine sensor responses to turbulent wind. In this paper, the model is validated both in time domain and frequency domain with a nonlinear aeroservoelastic model. The approach is compared quantitatively against fatigue damage obtained from the power spectra of time...
Linear SVM-Based Android Malware Detection for Reliable IoT Services
Directory of Open Access Journals (Sweden)
Hyo-Sik Ham
2014-01-01
Full Text Available Current many Internet of Things (IoT services are monitored and controlled through smartphone applications. By combining IoT with smartphones, many convenient IoT services have been provided to users. However, there are adverse underlying effects in such services including invasion of privacy and information leakage. In most cases, mobile devices have become cluttered with important personal user information as various services and contents are provided through them. Accordingly, attackers are expanding the scope of their attacks beyond the existing PC and Internet environment into mobile devices. In this paper, we apply a linear support vector machine (SVM to detect Android malware and compare the malware detection performance of SVM with that of other machine learning classifiers. Through experimental validation, we show that the SVM outperforms other machine learning classifiers.
Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems
Nguyen, Chuong Hoang; Leonessa, Alexander
2017-08-01
In this paper, the problem of characterizing adaptive output feedback control laws for a general class of unknown MIMO linear systems is considered. Specifically, the presented control approach relies on three components, i.e., a predictor, a reference model and a controller. The predictor is designed to predict the system's output with arbitrary accuracy, for any admissible control input. Subsequently, a full state feedback control law is designed to control the predictor output to approach the reference system, while the reference system tracks the desired trajectory. Ultimately, the control objective of driving the actual system output to track the desired trajectories is achieved by showing that the system output, the predictor output and the reference system trajectories all converge to each other.
Torque ripple reduction of brushless DC motor based on adaptive input-output feedback linearization.
Shirvani Boroujeni, M; Markadeh, G R Arab; Soltani, J
2017-09-01
Torque ripple reduction of Brushless DC Motors (BLDCs) is an interesting subject in variable speed AC drives. In this paper at first, a mathematical expression for torque ripple harmonics is obtained. Then for a non-ideal BLDC motor with known harmonic contents of back-EMF, calculation of desired reference current amplitudes, which are required to eliminate some selected harmonics of torque ripple, are reviewed. In order to inject the reference harmonic currents to the motor windings, an Adaptive Input-Output Feedback Linearization (AIOFBL) control is proposed, which generates the reference voltages for three phases voltage source inverter in stationary reference frame. Experimental results are presented to show the capability and validity of the proposed control method and are compared with the vector control in Multi-Reference Frame (MRF) and Pseudo-Vector Control (P-VC) method results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Linear and support vector regressions based on geometrical correlation of data
Directory of Open Access Journals (Sweden)
Kaijun Wang
2007-10-01
Full Text Available Linear regression (LR and support vector regression (SVR are widely used in data analysis. Geometrical correlation learning (GcLearn was proposed recently to improve the predictive ability of LR and SVR through mining and using correlations between data of a variable (inner correlation. This paper theoretically analyzes prediction performance of the GcLearn method and proves that GcLearn LR and SVR will have better prediction performance than traditional LR and SVR for prediction tasks when good inner correlations are obtained and predictions by traditional LR and SVR are far away from their neighbor training data under inner correlation. This gives the applicable condition of GcLearn method.
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Perks, J; Benedict, S [UC Davis Cancer Center, Sacramento, CA (United States); Lucero, S [UC Davis, Davis, CA (United States)
2015-06-15
Purpose: To document the support of radiobiological small animal research by a modern radiation oncology facility. This study confirms that a standard, human use linear accelerator can cover the range of experiments called for by researchers performing animal irradiation. A number of representative, anthropomorphic murine phantoms were made. The phantoms confirmed the small field photon and electron beams dosimetry validated the use of the linear accelerator for rodents. Methods: Laser scanning a model, CAD design and 3D printing produced the phantoms. The phantoms were weighed and CT scanned to judge their compatibility to real animals. Phantoms were produced to specifically mimic lung, gut, brain, and othotopic lesion irradiations. Each phantom was irradiated with the same protocol as prescribed to the live animals. Delivered dose was measured with small field ion chambers, MOS/FETs or TLDs. Results: The density of the phantom material compared to density range across the real mice showed that the printed material would yield sufficiently accurate measurements when irradiated. The whole body, lung and gut irradiations were measured within 2% of prescribed doses with A1SL ion chamber. MOSFET measurements of electron irradiations for the orthotopic lesions allowed refinement of the measured small field output factor to better than 2% and validated the immunology experiment of irradiating one lesion and sparing another. Conclusion: Linacs are still useful tools in small animal bio-radiation research. This work demonstrated a strong role for the clinical accelerator in small animal research, facilitating standard whole body dosing as well as conformal treatments down to 1cm field. The accuracy of measured dose, was always within 5%. The electron irradiations of the phantom brain and flank tumors needed adjustment; the anthropomorphic phantoms allowed refinement of the initial output factor measurements for these fields which were made in a large block of solid water.
Directory of Open Access Journals (Sweden)
Haodong Yuan
2017-01-01
Full Text Available A novel bearing fault diagnosis method based on improved locality-constrained linear coding (LLC and adaptive PSO-optimized support vector machine (SVM is proposed. In traditional LLC, each feature is encoded by using a fixed number of bases without considering the distribution of the features and the weight of the bases. To address these problems, an improved LLC algorithm based on adaptive and weighted bases is proposed. Firstly, preliminary features are obtained by wavelet packet node energy. Then, dictionary learning with class-wise K-SVD algorithm is implemented. Subsequently, based on the learned dictionary the LLC codes can be solved using the improved LLC algorithm. Finally, SVM optimized by adaptive particle swarm optimization (PSO is utilized to classify the discriminative LLC codes and thus bearing fault diagnosis is realized. In the dictionary leaning stage, other methods such as selecting the samples themselves as dictionary and K-means are also conducted for comparison. The experiment results show that the LLC codes can effectively extract the bearing fault characteristics and the improved LLC outperforms traditional LLC. The dictionary learned by class-wise K-SVD achieves the best performance. Additionally, adaptive PSO-optimized SVM can greatly enhance the classification accuracy comparing with SVM using default parameters and linear SVM.
DEFF Research Database (Denmark)
Pham, Ninh Dang; Pagh, Rasmus
2012-01-01
projection-based technique that is able to estimate the angle-based outlier factor for all data points in time near-linear in the size of the data. Also, our approach is suitable to be performed in parallel environment to achieve a parallel speedup. We introduce a theoretical analysis of the quality...... of approximation to guarantee the reliability of our estimation algorithm. The empirical experiments on synthetic and real world data sets demonstrate that our approach is efficient and scalable to very large high-dimensional data sets....
Self-assembly behavior of a linear-star supramolecular amphiphile based on host-guest complexation.
Wang, Juan; Wang, Xing; Yang, Fei; Shen, Hong; You, Yezi; Wu, Decheng
2014-11-04
A star polymer, β-cyclodextrin-poly(l-lactide) (β-CD-PLLA), and a linear polymer, azobenzene-poly(ethylene glycol) (Azo-PEG), could self-assemble into a supramolecular amphiphilic copolymer (β-CD-PLLA@Azo-PEG) based on the host-guest interaction between β-CD and azobenzene moieties. This linear-star supramolecular amphiphilic copolymer further self-assembled into a variety of morphologies, including sphere-like micelle, carambola-like micelle, naan-like micelle, shuttle-like lamellae, tube-like fiber, and random curled-up lamellae, by tuning the length of hydrophilic or hydrophobic chains. The variation of morphology was closely related to the topological structure and block ratio of the supramolecular amphiphiles. These self-assembly structures could disassemble upon an ultraviolet (UV) light irradiation.
Barrett, C. A.
1985-01-01
Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.
Liu, Fenglin; Cong, Wenxiang; Wang, Ge
2013-01-01
Purpose: The goal is to develop a new architecture for computed tomography (CT) which is at an ultra-low-dose for developing countries, especially in rural areas. Methods: The proposed scheme is inspired by the recently developed compressive sensing and interior tomography techniques, where the data acquisition system targets a region of interest (ROI) to acquire limited and truncated data. The source and detector are translated in opposite directions for either ROI reconstruction with one or more localized linear scans or global reconstruction by combining multiple ROI reconstructions. In other words, the popular slip ring is replaced by a translation based setup, and the instrumentation cost is reduced by a relaxation of the imaging speed requirement. Results: The various translational scanning modes are theoretically analyzed, and the scanning parameters are optimized. The numerical simulation results from different numbers of linear scans confirm the feasibility of the proposed scheme, and suggest two pre...
Pascual, Javier; Velasco-Alvarez, Francisco; Muller, Klaus-Robert; Vidaurre, Carmen
2012-01-01
In this study we show how healthy subjects are able to use a non-invasive Motor Imagery (MI)-based Brain Computer Interface (BCI) to achieve linear control of an upper-limb neuromuscular electrical stimulation (NMES) controlled neuroprosthesis in a simple binary target selection task. Linear BCI control can be achieved if two motor imagery classes can be discriminated with a reliability over 80% in single trial. The results presented in this work show that there was no significant loss of performance using the neuroprosthesis in comparison to MI where no stimulation was present. However, it is remarkable how different the experience of the users was in the same experiment. The stimulation either provoked a positive reinforcement feedback, or prevented the user from concentrating in the task.
Ji, Yanju; Huang, Wanyu; Yu, Mingmei; Guan, Shanshan; Wang, Yuan; Zhu, Yu
2017-01-01
This article studies full-waveform associated identification method of airborne time-domain electromagnetic method (ATEM) 3-d anomalies based on multiple linear regression analysis method. By using convolution algorithm, full-waveform theoretical responses are computed to derive sample library including switch-off-time period responses and off-time period responses. Extract full-waveform attributes from theoretical responses to derive linear regression equations which are used to identify the geological parameters. In order to improve the precision ulteriorly, we optimize the identification method by separating the sample library into different groups and identify the parameter respectively. Performance of full-waveform associated identification method with field data of wire-loop test experiments with ATEM system in Daedao of Changchun proves that the full-waveform associated identification method is feasible practically.
Directory of Open Access Journals (Sweden)
Caiping Zhang
2013-05-01
Full Text Available Battery model identification is very important for reliable battery management as well as for battery system design process. The common problem in identifying battery models is how to determine the most appropriate mathematical model structure and parameterized coefficients based on the measured terminal voltage and current. This paper proposes a novel semiparametric approach using the wavelet-based partially linear battery model (PLBM and a recursive penalized wavelet estimator for online battery model identification. Three main contributions are presented. First, the semiparametric PLBM is proposed to simulate the battery dynamics. Compared with conventional electrical models of a battery, the proposed PLBM is equipped with a semiparametric partially linear structure, which includes a parametric part (involving the linear equivalent circuit parameters and a nonparametric part [involving the open-circuit voltage (OCV]. Thus, even with little prior knowledge about the OCV, the PLBM can be identified using a semiparametric identification framework. Second, we model the nonparametric part of the PLBM using the truncated wavelet multiresolution analysis (MRA expansion, which leads to a parsimonious model structure that is highly desirable for model identification; using this model, the PLBM could be represented in a linear-in-parameter manner. Finally, to exploit the sparsity of the wavelet MRA representation and allow for online implementation, a penalized wavelet estimator that uses a modified online cyclic coordinate descent algorithm is proposed to identify the PLBM in a recursive fashion. The simulation and experimental results demonstrate that the proposed PLBM with the corresponding identification algorithm can accurately simulate the dynamic behavior of a lithium-ion battery in the Federal Urban Driving Schedule tests.
Particle velocity gradient based acoustic mode beamforming for short linear vector sensor arrays.
Gur, Berke
2014-06-01
In this paper, a subtractive beamforming algorithm for short linear arrays of two-dimensional particle velocity sensors is described. The proposed method extracts the highly directional acoustic modes from the spatial gradients of the particle velocity field measured at closely spaced sensors along the array. The number of sensors in the array limits the highest order of modes that can be extracted. Theoretical analysis and numerical simulations indicate that the acoustic mode beamformer achieves directivity comparable to the maximum directivity that can be obtained with differential microphone arrays of equivalent aperture. When compared to conventional delay-and-sum beamformers for pressure sensor arrays, the proposed method achieves comparable directivity with 70%-85% shorter apertures. Moreover, the proposed method has additional capabilities such as high front-back (port-starboard) discrimination, frequency and steer direction independent response, and robustness to correlated ambient noise. Small inter-sensor spacing that results in very compact apertures makes the proposed beamformer suitable for space constrained applications such as hearing aids and short towed arrays for autonomous underwater platforms.
Research on detecting heterogeneous fibre from cotton based on linear CCD camera
Zhang, Xian-bin; Cao, Bing; Zhang, Xin-peng; Shi, Wei
2009-07-01
The heterogeneous fibre in cotton make a great impact on production of cotton textile, it will have a bad effect on the quality of product, thereby affect economic benefits and market competitive ability of corporation. So the detecting and eliminating of heterogeneous fibre is particular important to improve machining technics of cotton, advance the quality of cotton textile and reduce production cost. There are favorable market value and future development for this technology. An optical detecting system obtains the widespread application. In this system, we use a linear CCD camera to scan the running cotton, then the video signals are put into computer and processed according to the difference of grayscale, if there is heterogeneous fibre in cotton, the computer will send an order to drive the gas nozzle to eliminate the heterogeneous fibre. In the paper, we adopt monochrome LED array as the new detecting light source, it's lamp flicker, stability of luminous intensity, lumens depreciation and useful life are all superior to fluorescence light. We analyse the reflection spectrum of cotton and various heterogeneous fibre first, then select appropriate frequency of the light source, we finally adopt violet LED array as the new detecting light source. The whole hardware structure and software design are introduced in this paper.
A Detail Based Method for Linear Full Reference Image Quality Prediction.
Di Claudio, Elio D; Jacovitti, Giovanni
2017-09-27
In this paper, a novel Full Reference method is proposed for image quality assessment, using the combination of two separate metrics to measure the perceptually distinct impact of detail losses and of spurious details. To this purpose, the gradient of the impaired image is locally decomposed as a predicted version of the original gradient, plus a gradient residual. It is assumed that the detail attenuation identifies the detail loss, whereas the gradient residuals describe the spurious details. It turns out that the perceptual impact of detail losses is roughly linear with the loss of the positional Fisher information, while the perceptual impact of the spurious details is roughly proportional to a logarithmic measure of the signal to residual ratio. The affine combination of these two metrics forms a new index strongly correlated with the empirical Differential Mean Opinion Score (DMOS) for a significant class of image impairments, as verified for three independent popular databases. The method allowed alignment and merging of DMOS data coming from these different databases to a common DMOS scale by affine transformations. Unexpectedly, the DMOS scale setting is possible by the analysis of a single image affected by additive noise.
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Mohammad Ramezani
2011-01-01
Full Text Available Objective(sThe development of efficient and safe carrier system to transfer DNA into cells is essential in non-viral gene therapy. The aim of the present study was to evaluate the effect of linear polyetheneimine (lPEI (2500 Da on the physicochemical and biological properties of lipopolyplexes constructed from liposomes and lPEI. Materials and MethodsDifferent lipopolymers were synthesized from lPEI and acrylate derivatives. Nanocarriers were composed of the lipids (DOPE, DPPE and DOTAP and the synthesized lipopolymers. After characterization of the prepared vectors by determination of size and zeta potential, transfection activity was tested in Neuro2A cells. Ethidium bromide and MTT test were used to evaluate the DNA condensation ability and cytotoxicity of vectors, respectively. Results Vector’s size ranged from 95 to 337 nm and they had positive charge. The differences in DNA binding properties of lipopolyplexes were not significant. Among lipids, DOTAP showed better impact on transfection efficiency. The highest transfection activity was achieved by liposomal formulation consist of DOTAP and lipopolymer composed of lPEI and hexyl acrylate. The lipopolyplexes showed minimum cytotoxicity to the cultured cells in vitro. Conclusion The results of study confirmed that it is possible to improve gene expression using lipopolyplexes.
A Detail-Based Method for Linear Full Reference Image Quality Prediction
Di Claudio, Elio D.; Jacovitti, Giovanni
2018-01-01
In this paper, a novel Full Reference method is proposed for image quality assessment, using the combination of two separate metrics to measure the perceptually distinct impact of detail losses and of spurious details. To this purpose, the gradient of the impaired image is locally decomposed as a predicted version of the original gradient, plus a gradient residual. It is assumed that the detail attenuation identifies the detail loss, whereas the gradient residuals describe the spurious details. It turns out that the perceptual impact of detail losses is roughly linear with the loss of the positional Fisher information, while the perceptual impact of the spurious details is roughly proportional to a logarithmic measure of the signal to residual ratio. The affine combination of these two metrics forms a new index strongly correlated with the empirical Differential Mean Opinion Score (DMOS) for a significant class of image impairments, as verified for three independent popular databases. The method allowed alignment and merging of DMOS data coming from these different databases to a common DMOS scale by affine transformations. Unexpectedly, the DMOS scale setting is possible by the analysis of a single image affected by additive noise.
Study and development of a laser based alignment system for the compact linear collider
AUTHOR|(CDS)2083149
The first objective of the PhD thesis is to develop a new type of positioning sensor to align components at micrometre level over 200 m with respect to a laser beam as straight line reference. The second objective is to estimate the measurement accuracy of the total alignment system over 200 m. The context of the PhD thesis is the Compact Linear Collider project, which is a study for a future particle accelerator. The proposed positioning sensor is made of a camera and an open/close shutter. The sensor can measure the position of the laser beam with respect to its own coordinate system. To do a measurement, the shutter closes, a laser spot appears on it, the camera captures a picture of the laser spot and the coordinates of the laser spot centre are reconstructed in the sensor coordinate system with image processing. Such a measurement requires reference targets on the positioning sensor. To reach the rst objective of the PhD thesis, we used laser theory...
Evaluating Army Bases’ Ability to Support Maneuver Training: A Linear Programming Approach
1993-09-01
Army land. Grace Bukowski , coordinator for Citizen Alert, a Nevada based coalition that monitors government land use said [Ref. 2:p. 1C]: We’re saying if...OCSA, DACS-DM(TABS) (CPT Charles Fletcher) Washington, DC 20310-0412 7. Department of the Army 1 Base Realignment and Closure (BRAC) ATTN: ATCS-OR USA TRADOC Fort Monroe, VA 23651 54
Zhang, Hua; Kurgan, Lukasz
2014-12-01
Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.
Energy Technology Data Exchange (ETDEWEB)
Jammes, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France). Laboratoire d`Analyse et d`Architecture des Systemes; Dragos, A. [Bucharest Univ. Politechnica (Romania)
1998-11-01
In this paper, artificial neural networks are used to elaborate non-linear control of the average output voltage of Buck and Boost converters. The training of the regulator is based on the adjustment technique used by indirect adaptative command structures. These techniques require a system model and performances of inputs/outputs and state models are compared. It is shown that this approach allows to generate non-linear regulators for the converters under study, but it is preferable to introduce some modifications in order to facilitate the training of the regulator. (J.S.) 4 refs.
Linear precoding based on polynomial expansion: reducing complexity in massive MIMO.
Mueller, Axel; Kammoun, Abla; Björnson, Emil; Debbah, Mérouane
Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively "antenna-efficient" regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.
Linear precoding based on polynomial expansion: reducing complexity in massive MIMO
Mueller, Axel
2016-02-29
Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively “antenna-efficient” regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.
A program to compute geographical positions of underwater artifact based on linear measurements
Digital Repository Service at National Institute of Oceanography (India)
Ganesan, P.
While carrying out underwater positioning in shallow waters, the Diver Archaeologists measure lengths and bearings from a base line of the well-established control network to each and every corner of the artifact. A program in Basic language...
An upgradeable agent-based model to explore non-linearity and intangibles in peacekeeping operations
Lehmann, Wolfgang
2006-01-01
Peacekeeping operations (PKO) have become a significant challenge to the German Armed Forces. For the development of tactics, techniques, procedures and equipment with combat operations, agent-based models have been developed, used and exploited for many years. Modeling and simulation of PKO, however, is still in a very early stage. This thesis develops an agent-based model to analyze PKO. Unlike many other multi-agent systems (MAS), it implements the rules of discrete event simulation. The c...
Directory of Open Access Journals (Sweden)
Yujie Liang
2014-11-01
Full Text Available In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA estimation with distributed sparse linear arrays (SLAs and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach.
Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin
2014-11-20
In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach.
Tkaczyk, J. Eric; Haneda, Eri; Palma, Giovanni; Iordache, Razvan; Klausz, Remy; Garayt, Mathieu; Carton, Ann-Katherine
2014-03-01
Non-linear image processing and reconstruction algorithms that reduced noise while preserving edge detail are currently being evaluated in medical imaging research literature. We have implemented a robust statistics analysis of four widely utilized methods. This work demonstrates consistent trends in filter impact by which such non-linear algorithms can be evaluated. We calculate observer model test statistics and propose metrics based on measured non-Gaussian distributions that can serve as image quality measures analogous to SDNR and detectability. The filter algorithms that vary significantly in their approach to noise reduction include median (MD), bilateral (BL), anisotropic diffusion (AD) and total-variance regularization (TV). It is shown that the detectability of objects limited by Poisson noise is not significantly improved after filtration. There is no benefit to the fraction of correct responses in repeated n-alternate forced choice experiments, for n=2-25. Nonetheless, multi-pixel objects with contrast above the detectability threshold appear visually to benefit from non-linear processing algorithms. In such cases, calculations on highly repeated trials show increased separation of the object-level histogram from the background-level distribution. Increased conspicuity is objectively characterized by robust statistical measures of distribution separation.
Ueda, Yoshiaki; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji
2017-12-01
High performance of color quantization processing is very important for obtaining limited-color images with good quality. The median cut algorithm (MCA) is a typical color quantization method. Its computational cost is low owing to its simple algorithm, but the quality of output images is mediocre at best. In this paper, we describe a modification of MCA. In our method, we use a combination of principal component analysis (PCA) and linear discriminant analysis (LDA) to accomplish effective partitioning of color space. Concretely, PCA and LDA are used to calculate partitioning planes and their positions, respectively. We verify the effectiveness of our method through experiments using 24-bit full-color natural images.
Ueda, Yoshiaki; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji
2017-10-01
High performance of color quantization processing is very important for obtaining limited-color images with good quality. The median cut algorithm (MCA) is a typical color quantization method. Its computational cost is low owing to its simple algorithm, but the quality of output images is mediocre at best. In this paper, we describe a modification of MCA. In our method, we use a combination of principal component analysis (PCA) and linear discriminant analysis (LDA) to accomplish effective partitioning of color space. Concretely, PCA and LDA are used to calculate partitioning planes and their positions, respectively. We verify the effectiveness of our method through experiments using 24-bit full-color natural images.
Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines
Directory of Open Access Journals (Sweden)
Lara del Val
2015-06-01
Full Text Available Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM. The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.
Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay
2014-05-01
In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the
Linear spectral modeling of ground-based observations of Europa (ESO/VLT/SINFONI)
Ligier, Nicolas; Poulet, François; Carter, John; Langevin, Yves; Dumas, Christophe; Gourgeot, Florian
2015-11-01
Jupiter’s moon Europa may harbor a global salty subsurface liquid water ocean (Kivelson et al. 2000), and its surface should contain important clues about its composition. However, debate still persists about the nature of the surface chemistry and the relative roles of exogenous versus endogenous processing. Recently, Roth et al. (2014) reported the presence of activity by the detection of plumes reinforcing Europa as a major target of interests of upcoming space missions such as the ESA L-class mission JUICE.To continue the investigation of the composition of the surface of Europa, a global mapping campaign of the satellite was performed between October 2011 and January 2012 with the integral field spectrograph SINFONI on the Very Large Telescope (VLT) in Chile. The high spectral binning of this instrument (0.5 nm) is suitable to detect any narrow signature in the wavelength range 1.45-2.45 μm. The spatially resolved spectra we obtained over five epochs nearly cover the entire surface of Europa with a pixel scale of 12.5 by 25 m.a.s (~35 by 70 km on Europa’s surface).We perform linear spectral modeling using 4 types of species : water-ice (both crystalline and amorphous), sulfuric acid hydrate, sulfate salts and Cl-rich salts. At first order, spectra on the leading side are, as expected, dominated by water-ice distorted and asymmetric absorption features, whereas sulfuric acid hydrate thought to originate from Iogenic sulfur ion bombardment is clearly predominant on the trailing side (Carlson et al. 2005).Salts are also required to fit any SINFONI spectrum with the following notable result: when Na/K-bearing chlorines instead of Mg-sulfates are used, the fits are improved whatever the region. The feature centered at ~2.07 µm previously associated to the magnesium sulfates (Brown et al. 2013) is also observed in the SINFONI spectra and can be reproduced by some chlorine salts. Global abundance maps will be presented, regional variations of abundances will be
Solowey, Douglas P.; Mane, Manoj V.; Kurogi, Takashi; Carroll, Patrick J.; Manor, Brian C.; Baik, Mu-Hyun; Mindiola, Daniel J.
2017-11-01
Selectively converting linear alkanes to α-olefins under mild conditions is a highly desirable transformation given the abundance of alkanes as well as the use of olefins as building blocks in the chemical community. Until now, this reaction has been primarily the remit of noble-metal catalysts, despite extensive work showing that base-metal alkylidenes can mediate the reaction in a stoichiometric fashion. Here, we show how the presence of a hydrogen acceptor, such as the phosphorus ylide, when combined with the alkylidene complex (PNP)Ti=CHtBu(CH3) (PNP=N[2-P(CHMe2)2-4-methylphenyl]2‑), catalyses the dehydrogenation of cycloalkanes to cyclic alkenes, and linear alkanes with chain lengths of C4 to C8 to terminal olefins under mild conditions. This Article represents the first example of a homogeneous and selective alkane dehydrogenation reaction using a base-metal titanium catalyst. We also propose a unique mechanism for the transfer dehydrogenation of hydrocarbons to olefins and discuss a complete cycle based on a combined experimental and computational study.
Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara
2017-01-01
In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.
Generation of pulsed light in the visible spectral region based on non-linear cavity dumping
DEFF Research Database (Denmark)
Johansson, Sandra; Andersen, Martin; Tidemand-Lichtenberg, Peter
We propose a novel generic approach for generation of pulsed light in the visible spectrum based on sum-frequency generation between the high circulating intra-cavity power of a high finesse CW laser and a single-passed pulsed laser. For demonstration, we used a CW 1342 nm laser mixed with a pass...
Multi-Site Calibration of Linear Reservoir Based Geomorphologic Rainfall-Runoff Models
Directory of Open Access Journals (Sweden)
Bahram Saeidifarzad
2014-09-01
Full Text Available Multi-site optimization of two adapted event-based geomorphologic rainfall-runoff models was presented using Non-dominated Sorting Genetic Algorithm (NSGA-II method for the South Fork Eel River watershed, California. The first model was developed based on Unequal Cascade of Reservoirs (UECR and the second model was presented as a modified version of Geomorphological Unit Hydrograph based on Nash’s model (GUHN. Two calibration strategies were considered as semi-lumped and semi-distributed for imposing (or unimposing the geomorphology relations in the models. The results of models were compared with Nash’s model. Obtained results using the observed data of two stations in the multi-site optimization framework showed reasonable efficiency values in both the calibration and the verification steps. The outcomes also showed that semi-distributed calibration of the modified GUHN model slightly outperformed other models in both upstream and downstream stations during calibration. Both calibration strategies for the developed UECR model during the verification phase showed slightly better performance in the downstream station, but in the upstream station, the modified GUHN model in the semi-lumped strategy slightly outperformed the other models. The semi-lumped calibration strategy could lead to logical lag time parameters related to the basin geomorphology and may be more suitable for data-based statistical analyses of the rainfall-runoff process.
Region specific optimization of continuous linear attenuation coefficients based on UTE (RESOLUTE)
DEFF Research Database (Denmark)
Ladefoged, Claes N; Benoit, Didier; Law, Ian
2015-01-01
images were evaluated in the whole brain, as well as regionally in the brain using a ROI-based analysis. Our method segments air, brain, cerebral spinal fluid, and soft tissue voxels on the unprocessed UTE TE images, and uses a mapping of R(*)2 values to CT Hounsfield Units (HU) to measure the density...
Shen, Y.; Tauritz, J.L.
2005-01-01
Traditionally, Taylor series models are only used under small signal or mildly nonlinear regimes. In this paper, a new behavioral model for microwave power amplifiers (PAs) based on first order Taylor expansion of multivariable nonlinearities and interpolation is proposed. The model is tailored for
Support-Vector-based Least Squares for learning non-linear dynamics
de Kruif, B.J.; de Vries, Theodorus J.A.
2002-01-01
A function approximator is introduced that is based on least squares support vector machines (LSSVM) and on least squares (LS). The potential indicators for the LS method are chosen as the kernel functions of all the training samples similar to LSSVM. By selecting these as indicator functions the
Non-linear model based control of a propylene polymerization reactor
Al-Haj Ali, M.; Betlem, B.; Weickert, G.; Roffel, B.
2007-01-01
A modified generic model controller is developed and tested through a simulation study. The application involves model-based control of a propylene polymerization reactor in which the monomer conversion and melt index of the produced polymer are controlled by manipulating the reactor cooling water
Robust Feedback Linearization-based Control Design for a Wheeled Mobile Robot
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Andersen, Palle; Pedersen, Tom Søndergaard
2002-01-01
This paper considers the trajectory tracking problem for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The robot is modeled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. A nonlinear trajectory tracking feedback control law based...
Robust Feedback Linearization-based Control Design for a Wheeled Mobile Robot
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Andersen, Palle; Pedersen, Tom Søndergaard
This paper considers the trajectory tracking problem for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The robot is modeled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. A nonlinear trajectory tracking feedback control law based...
van Berkel, M.; Kobayashi, T.; Igami, H.; Vandersteen, G.; Hogeweij, G. M. D.; Tanaka, K.; Tamura, N.; Zwart, H. J.; Kubo, S.; Ito, S.; Tsuchiya, H.; de Baar, M. R.; The LHD Experiment Group
2017-12-01
A new methodology to analyze non-linear components in perturbative transport experiments is introduced. The methodology has been experimentally validated in the Large Helical Device for the electron heat transport channel. Electron cyclotron resonance heating with different modulation frequencies by two gyrotrons has been used to directly quantify the amplitude of the non-linear component at the inter-modulation frequencies. The measurements show significant quadratic non-linear contributions and also the absence of cubic and higher order components. The non-linear component is analyzed using the Volterra series, which is the non-linear generalization of transfer functions. This allows us to study the radial distribution of the non-linearity of the plasma and to reconstruct linear profiles where the measurements were not distorted by non-linearities. The reconstructed linear profiles are significantly different from the measured profiles, demonstrating the significant impact that non-linearity can have.
〈Original Papers〉Non-Linear Note Taking Based on Mind Map for Efficient Reading
HONKE, Yoshifumi
2011-01-01
[Abstract] We are expected to read a variety of books at school or job for various purposes. Many of us start reading from on page one and take information one after each other trying to understand the contents without doubting whether that reading style is the best. We generally make notes in sentence-based line structures without doubting whether that style is the best. Few people recognize such conventional styles might be considered useless work and wasting time. This paper will investiga...
Linear Fresnel Reflector based Solar Radiation Concentrator for Combined Heating and Power
Chatterjee, Aveek; Bernal, Eva; Seshadri, Satya; Mayer, Oliver; Greaves, Mikal
2011-12-01
We have designed and realized a test rig to characterize concentrated solar-based CHP (combined heat and power) generator. Cost benefit analysis has been used to compare alternate technologies, which can cogenerate electrical and thermal power. We have summarized the experimental setup and methods to characterize a concentrated solar thermal (CST) unit. In this paper, we demonstrate the performance data of a concentrated solar thermal system.
On the Occurrence of Liquation During Linear Friction Welding of Ni-Based Superalloys
Masoumi, F.; Shahriari, D.; Jahazi, M.; Cormier, J.; Flipo, B. C. D.
2017-06-01
A combination of experimental and analytical methods was used to study the possible occurrence of liquation during LFW of the newly developed AD730TM Ni-based superalloy. LFWed joints were produced using a semi-industrial size facility and the interfaces of the joints as well as the ejected flash were examined using optical and Field Emission Gun Scanning Electron Microscopy (FEG-SEM). Physical simulation of the LFW thermal cycle, using thermomechanical simulator Gleeble™ 3800, showed that incipient melting started from 1473 K (1200 °C). The analytical model, calibrated by experiments, predicted that the highest temperature of the interface was about 1523 K (1250 °C). The constitutive equations based on lattice and pipe diffusion models were developed to quantify the self-diffusivity of the elements and control the extent of liquation by considering the effect of LFW process parameters. Analytical results show that the application of compressive stresses during LFW results in 25 times increase in the diffusion of Ni atoms at the weld interface. Therefore, no presence of re-solidified phases, i.e., occurrence of liquation, was observed in the microstructure of the weld zone or the flash in the present study. Based on the obtained results, a methodology was developed for designing the optimum pressure above which no liquation, and hence cracking, will be observable.
Energy Technology Data Exchange (ETDEWEB)
Iliopoulos, AS; Sun, X [Duke University, Durham, North Carolina (United States); Pitsianis, N [Aristotle University of Thessaloniki (Greece); Duke University, Durham, North Carolina (United States); Yin, FF; Ren, L
2016-06-15
Purpose: To address and lift the limited degree of freedom (DoF) of globally bilinear motion components such as those based on principal components analysis (PCA), for encoding and modeling volumetric deformation motion. Methods: We provide a systematic approach to obtaining a multi-linear decomposition (MLD) and associated motion model from deformation vector field (DVF) data. We had previously introduced MLD for capturing multi-way relationships between DVF variables, without being restricted by the bilinear component format of PCA-based models. PCA-based modeling is commonly used for encoding patient-specific deformation as per planning 4D-CT images, and aiding on-board motion estimation during radiotherapy. However, the bilinear space-time decomposition inherently limits the DoF of such models by the small number of respiratory phases. While this limit is not reached in model studies using analytical or digital phantoms with low-rank motion, it compromises modeling power in the presence of relative motion, asymmetries and hysteresis, etc, which are often observed in patient data. Specifically, a low-DoF model will spuriously couple incoherent motion components, compromising its adaptability to on-board deformation changes. By the multi-linear format of extracted motion components, MLD-based models can encode higher-DoF deformation structure. Results: We conduct mathematical and experimental comparisons between PCA- and MLD-based models. A set of temporally-sampled analytical trajectories provides a synthetic, high-rank DVF; trajectories correspond to respiratory and cardiac motion factors, including different relative frequencies and spatial variations. Additionally, a digital XCAT phantom is used to simulate a lung lesion deforming incoherently with respect to the body, which adheres to a simple respiratory trend. In both cases, coupling of incoherent motion components due to a low model DoF is clearly demonstrated. Conclusion: Multi-linear decomposition can
Giaccu, Gian Felice; Caracoglia, Luca
2017-04-01
Pre-tensioned-cable bracing systems are widely employed in structural engineering to limit lateral deflections and stabilize structures. A suitable configuration of the pre-tensioned-cable bracing systems in a structure is an important issue since the internal force distribution, emerging from the interaction with the existing structure, significantly affects the structural dynamic behavior. The design, however, is often based on the intuition and the previous experience of the engineer. In recent years, the authors have been investigating the non-linear dynamic response of cable systems, installed on cable-stayed bridges, and in particular the so-called ;cable-cross-tie systems; forming a cable network. The bracing cables (cross-ties) can exhibit slackening or snapping. Therefore, a non-linear unilateral model, combined with the taut-cable theory, is required to simulate the incipient slackening conditions in the stays. Capitalizing from this work on non-linear cable dynamics, this paper proposes a new approach to analyze, in laterally- braced truss structures, the unilateral effects and dynamic response accounting for the loss in the pre-tensioning force imparted to the bracing cables. This effect leads to non-linear vibration of the structure. In this preliminary study, the free vibrations of the structure are investigated by using the ;Equivalent Linearization Method;. A performance coefficient, a real positive number between 0.5 and 1.0, is defined and employed to monitor the relative reduction in the apparent stiffness of the braces during structural vibration, ;mode by mode;. It is shown that the system can exhibit alternate unilateral behavior of the cross-braces. A reduction of the performance coefficient close to fifty percent is observed in the braces when the initial pre-tensioning force is small. On the other hand the performance coefficient tends to one in the case of a high level of pre-stress. It is concluded that the performance coefficient may
Prosperi, Mattia C F; Altmann, Andre; Rosen-Zvi, Michal; Aharoni, Ehud; Borgulya, Gabor; Bazso, Fulop; Sönnerborg, Anders; Schülter, Eugen; Struck, Daniel; Ulivi, Giovanni; Vandamme, Anne-Mieke; Vercauteren, Jurgen; Zazzi, Maurizio
2009-01-01
The extreme flexibility of the HIV type-1 (HIV-1) genome makes it challenging to build the ideal antiretroviral treatment regimen. Interpretation of HIV-1 genotypic drug resistance is evolving from rule-based systems guided by expert opinion to data-driven engines developed through machine learning methods. The aim of the study was to investigate linear and non-linear statistical learning models for classifying short-term virological outcome of antiretroviral treatment. To optimize the model, different feature selection methods were considered. Robust extra-sample error estimation and different loss functions were used to assess model performance. The results were compared with widely used rule-based genotypic interpretation systems (Stanford HIVdb, Rega and ANRS). A set of 3,143 treatment change episodes were extracted from the EuResist database. The dataset included patient demographics, treatment history and viral genotypes. A logistic regression model using high order interaction variables performed better than rule-based genotypic interpretation systems (accuracy 75.63% versus 71.74-73.89%, area under the receiver operating characteristic curve [AUC] 0.76 versus 0.68-0.70) and was equivalent to a random forest model (accuracy 76.16%, AUC 0.77). However, when rule-based genotypic interpretation systems were coupled with additional patient attributes, and the combination was provided as input to the logistic regression model, the performance increased significantly, becoming comparable to the fully data-driven methods. Patient-derived supplementary features significantly improved the accuracy of the prediction of response to treatment, both with rule-based and data-driven interpretation systems. Fully data-driven models derived from large-scale data sources show promise as antiretroviral treatment decision support tools.
Consistency analysis of subspace identification methods based on a linear regression approach
DEFF Research Database (Denmark)
Knudsen, Torben
2001-01-01
not include important model structures as e.g. Box-Jenkins. Based on a simple least squares approach this paper shows the possible inconsistency under the weak assumptions and develops only slightly stricter assumptions sufficient for consistency and which includes any model structure......In the literature results can be found which claim consistency for the subspace method under certain quite weak assumptions. Unfortunately, a new result gives a counter example showing inconsistency under these assumptions and then gives new more strict sufficient assumptions which however does...
Impedance cardiography filtering using scale Fourier linear combiner based on RLS algorithm.
Dromer, O; Alata, O; Bernard, O
2009-01-01
The Cardiac Output (CO) can be calculated from the thoracic cardio-impedance signal from several methods, and all of them are linked to the frequency information, information that is limited by the type of filtering used before. A methodology is proposed to evaluate the effect of the commonly used methods of filtering, and an improvement of the SFLC LMS-based algorithm by the use of RLS algorithm is also tested. Performances of algorithms are then evaluated considering different types of noise such as white noise or combination of sinusoidal noises to simulate the effect of respiration and body movements.
Directory of Open Access Journals (Sweden)
Xiaoling Zhang
2013-01-01
Full Text Available The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers’ preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of “low risk and high return efficiency” in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.
Directory of Open Access Journals (Sweden)
G.M. Golenkov
2015-12-01
Full Text Available Purpose. The research of the influence of value and direction of current on the equivalent spring magnetic force based on coaxial-linear motor (CLM – MS. Methodology. We carried out investigation of the equivalent harshness of magnetic spring with determination of electromechanical propulsion performance characteristics by the methods of computer modeling and experimental research of physical model of CLM – MS. The modeling of magnetic spring of CLM – MS is carried out by the finite-element method. The challenge is met as an axisymmetric challenge in cylindrical co-ordinates in magnetostatic approach. The experimental investigattion of the propulsion performance characteristics of magnetic spring is carried out on the test bench. Results. After the computer modeling and the experimental investigation of the electromechanical propulsion performance characteristics of magnetic spring the expressions of equivalent stiffness coefficient depending on the current in winding are obtained. The results of computer modeling are confirmed experimentally. Originality. The determination of equivalent stiffness coefficient of magnetic spring of vibration exciter based on coaxial-linear motor. Practical value. The obtained determination of equivalent stiffness coefficient of magnetic spring may be used in process of designing of vibration machines with devices for change of natural oscillation frequency.
Directory of Open Access Journals (Sweden)
Chenguang Shi
2016-12-01
Full Text Available This paper investigates the joint target parameter (delay and Doppler estimation performance of linear frequency modulation (LFM-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS component and weak isotropic scatterers (WIS components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR, target’s radar cross section (RCS and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component.
Zhang, Xiaoling; Huang, Kai; Zou, Rui; Liu, Yong; Yu, Yajuan
2013-01-01
The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of "low risk and high return efficiency" in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.
Liu, Kehui; Zhang, Jiyang; Fu, Bin; Xie, Hongwei; Wang, Yingchun; Qian, Xiaohong
2014-07-01
Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.
1998-01-01
The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.
Chen, Benyong; Zhang, Enzheng; Yan, Liping; Liu, Yanna
2014-10-01
Correct return of the measuring beam is essential for laser interferometers to carry out measurement. In the actual situation, because the measured object inevitably rotates or laterally moves, not only the measurement accuracy will decrease, or even the measurement will be impossibly performed. To solve this problem, a novel orthogonal return method for linearly polarized beam based on the Faraday effect is presented. The orthogonal return of incident linearly polarized beam is realized by using a Faraday rotator with the rotational angle of 45°. The optical configuration of the method is designed and analyzed in detail. To verify its practicability in polarization interferometry, a laser heterodyne interferometer based on this method was constructed and precision displacement measurement experiments were performed. These results show that the advantage of the method is that the correct return of the incident measuring beam is ensured when large lateral displacement or angular rotation of the measured object occurs and then the implementation of interferometric measurement can be ensured.
Modified reduced order observer based linear active disturbance rejection control for TITO systems.
Pawar, S N; Chile, R H; Patre, B M
2017-11-01
This paper proposes an observer based control approach for two input and two output (TITO) plant affected by the lumped disturbance which includes the undesirable effect of cross couplings, parametric uncertainties, and external disturbances. A modified reduced order extended state observer (ESO) based active disturbance rejection control (ADRC) is designed to estimate the lumped disturbance actively as an extended state and compensate its effect by adding it to the control. The decoupled mechanism has been used to determine the controller parameters, while the proposed control technique is applied to the TITO coupled plant without using decoupler to show its efficacy. Simulation results show that the proposed design is efficiently able to nullify the interactions within the loops in the multivariable process with better transient performance as compared to the existing proportional-integral-derivative (PID) control methods. An experimental application of two tanks multivariable level control system is investigated to present the validity of proposed scheme. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Said-Houari, Belkacem
2017-01-01
This self-contained, clearly written textbook on linear algebra is easily accessible for students. It begins with the simple linear equation and generalizes several notions from this equation for the system of linear equations and introduces the main ideas using matrices. It then offers a detailed chapter on determinants and introduces the main ideas with detailed proofs. The third chapter introduces the Euclidean spaces using very simple geometric ideas and discusses various major inequalities and identities. These ideas offer a solid basis for understanding general Hilbert spaces in functional analysis. The following two chapters address general vector spaces, including some rigorous proofs to all the main results, and linear transformation: areas that are ignored or are poorly explained in many textbooks. Chapter 6 introduces the idea of matrices using linear transformation, which is easier to understand than the usual theory of matrices approach. The final two chapters are more advanced, introducing t...
Directory of Open Access Journals (Sweden)
Wikberg Jarl ES
2010-06-01
Full Text Available Abstract Background Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity. Results We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations to the respective combination's interaction dissociation constant (Kd. We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P2 = 0.67-0.73; for new kinases it ranged P2kin = 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P2 = 0.47, P2kin = 0.42 and AUC = 0.83. Conclusions Our results strongly support the applicability of proteochemometrics for kinome
Comment on “Beamstrahlung considerations in laser-plasma-accelerator-based linear colliders”
Directory of Open Access Journals (Sweden)
Valeri Lebedev
2013-10-01
Full Text Available Schroeder, Esarey, Geddes, Benedetti, and Leemans [Phys. Rev. ST Accel. Beams 13, 101301 (2010PRABFM1098-440210.1103/PhysRevSTAB.13.101301 and Phys. Rev. ST Accel. Beams 15, 051301 (2012PRABFM1098-440210.1103/PhysRevSTAB.15.051301] have proposed a set of parameters for a TeV-scale collider based on plasma wakefield accelerator principles. In particular, it is sugested that the luminosities greater than 10^{34} cm^{-2} s^{-1} are attainable for an electron-positron collider. In this Comment we dispute this set of parameters on the basis of first principles. The interactions of accelerating beam with plasma impose fundamental limitations on beam properties and, thus, on attainable luminosity values.
Marin, Cosmina Andreea; Kajzar, François; Manea-Saghin, Ana-Maria
2018-01-01
In this study, the synthesis and the characterization of new deoxyribonucleic acid (DNA) based compounds containing [2.2]paracyclophane moiety are reported. The DNA molecule was functionalized with hexadecyltrimethylammonium chloride (CTMA), [2.2]paracyclophane-4-methoxy-5-formyl [A] and [2.2]paracyclophane-4-hydroxy-5-formyl [B], respectively. These compounds were used for obtaining good optical quality thin films by spin coating method. The absorption and emission spectra of studied solutions and thin films showed that the new obtained materials are of good optical properties. The third-order nonlinear optical (NLO) properties of thin films were characterized by the optical third-harmonic generation technique at 1064.2 nm fundamental wavelength.
High-linearity piezoresistive response of mechanically strong graphene-based elastomer
Yuanzheng, Luo; Buyin, Li; Xiaoqi
2017-05-01
Traditional additive-free graphene bulk materials based on mono- three dimensional(3D) graphene networks type are fragile in most cases, which is unfavorable for their potential applications. Here we present compressible graphene foams (CGF) with superior properties endowed by the hierarchical porous structure, which taking graphene sheets as an inorganic embedding material and polyurethane sponge (PUS) as a polymer open-framework. The preparation process utilized a dip-coating method associated with directional freezing followed by lyophilization. The as-synthesized CGF not only possess a combination of ultralow density and excellent electrical conductivity, but it also can withstand large strains (>99%) without permanent deformation or fracture. We believe that these sponge/graphene embeddable multifunctional nanocomposites will expand practical applications of graphene monolith in the future.
Toward Model-Based Control of Non-linear Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Jensen, Tom Nørgaard; Kallesøe, Carsten
2013-01-01
. Following an analogy to electric circuits, first the mathematical expression for pressure drop over each component of the pipe network (WSS) such as pipes, pumps, valves and water towers is presented. Then the network model is derived based on the circuit theory and subsequently used for pressure management......Water leakage is an important component of water loss. Many methods have emerged from urban water supply systems (WSSs) for leakage control, but it still remains a challenge in many countries. Pressure management is an effective way to reduce the leakage in a system. It can also reduce the power...... consumption. To have a better understanding of leakage in WSSs, to control pressure and leakage effectively, and for optimal design of WSSs, suitable modeling is an important prerequisite. In this paper a model with the main objective of pressure control and consequently leakage reduction is presented...
DEFF Research Database (Denmark)
D'Souza, Sonia; Rasmussen, John; Schwirtz, Ansgar
2012-01-01
and valuable ergonomic tool. Objective: To investigate age and gender effects on the torque-producing ability in the knee and elbow in older adults. To create strength scaled equations based on age, gender, upper/lower limb lengths and masses using multiple linear regression. To reduce the number of dependent...... parameters based on statistical redundancies, and then validate these equations. Methods: 283 subjects (141 males, 142 females) aged 50-59 years (54.9 +/- 2.9) , 60-69 years (65.4 +/- 2.9) and 70-79 years (73.7 +/- 2.7) were tested for maximal voluntary isometric torque of right knee extensors and elbow...... flexors. Results: Males were signifantly stronger than females across all age groups. Elbow peak torque (EPT) was better preserved from 60s to 70s whereas knee peak torque (KPT) reduced significantly (P
Directory of Open Access Journals (Sweden)
T. J. Ma
2015-09-01
Full Text Available Three types of post-weld heat treatment (PWHT, i.e. solution treatment + primary aging + secondary aging (I, secondary aging (II, and primary aging + secondary aging (III, were applied to a single crystal nickel-based superalloy joint made with linear friction welding (LFW. The results show that the grains in the thermomechanically affected zone (TMAZ coarsen seriously and the primary γ' phase in the TMAZ precipitates unevenly after PWHT I. The primary γ' phase in the TMAZ and weld zone (WZ precipitates insufficiently and fine granular secondary γ' phase is observed in the matrix after PWHT II. After PWHT III, the primary γ' phase precipitates more sufficiently and evenly compared to PWHTs I and II. Moreover, the grains in the TMAZ have not coarsened seriously and fine granular secondary γ' phase is not found after PWHT III. PWHT III seems more suitable to the LFWed single crystal nickel-based superalloy joints when performing PWHT.
Directory of Open Access Journals (Sweden)
Richard Ottermanns
Full Text Available In this study we present evidence that anthropogenic stressors can reduce the resilience of age-structured populations. Enhancement of disturbance in a model-based Daphnia population lead to a repression of chaotic population dynamics at the same time increasing the degree of synchrony between the population's age classes. Based on the theory of chaos-mediated survival an increased risk of extinction was revealed for this population exposed to high concentrations of a chemical stressor. The Lyapunov coefficient was supposed to be a useful indicator to detect disturbance thresholds leading to alterations in population dynamics. One possible explanation could be a discrete change in attractor orientation due to external disturbance. The statistical analysis of Lyapunov coefficient distribution is proposed as a methodology to test for significant non-linear effects of general disturbance on populations. Although many new questions arose, this study forms a theoretical basis for a dynamical definition of population recovery.
Kok, Maarten O; Vaandrager, Lenneke; Bal, Roland; Schuit, Jantine
2012-03-01
While attempts are being made to improve health promotion by following a linear Evidence-Based (EB) approach, the actors involved are aware that the quality of health promotion is not just a matter of supplying 'evidence-based' interventions to local practitioners, but the result of a situated coproduction process that depends on many factors. This paper explores what constitutes an intervention that works from the perspective of health promotion professionals (HPP), and how, according to them, the development and implementation of interventions should be improved. We interviewed 81 HPPs about the use of 10 health promotion interventions at 30 Municipality Health Services in The Netherlands. The HPPs described an intervention that works as something that produces its intended effects after being realized in a local situation. Interventions are realized by combining elements of a supplied intervention (e.g. a theory, artefacts) with elements that are situated in the local context (e.g. funding, local network). Interventions that are transferred contain implicit assumptions about local contexts, but it is often unclear what precisely constitutes an intervention and what is assumed of local contexts. An intervention that works is a situated configuration of aligned elements. A linear EB approach depends on the realization of the local circumstances in which 'evidence based' interventions can work. Various strategies are possible for approximating such circumstances, but the core assumption that the configuration that is realized in practice is similar to the 'evidence based' intervention seems unrealistic for most health promotion in The Netherlands. Under such circumstances, attention should shift from central quality assurance to the system of actors and the distributed actions and heterogeneous learning processes that together add up to interventions that work. Copyright Â© 2012 Elsevier Ltd. All rights reserved.
Yanti, Y. R.; Amin, S. M.; Sulaiman, R.
2018-01-01
This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.
Interpretable exemplar-based shape classification using constrained sparse linear models.
Sigurdsson, Gunnar A; Yang, Zhen; Tran, Trac D; Prince, Jerry L
2015-02-01
Many types of diseases manifest themselves as observable changes in the shape of the affected organs. Using shape classification, we can look for signs of disease and discover relationships between diseases. We formulate the problem of shape classification in a holistic framework that utilizes a lossless scalar field representation and a non-parametric classification based on sparse recovery. This framework generalizes over certain classes of unseen shapes while using the full information of the shape, bypassing feature extraction. The output of the method is the class whose combination of exemplars most closely approximates the shape, and furthermore, the algorithm returns the most similar exemplars along with their similarity to the shape, which makes the result simple to interpret. Our results show that the method offers accurate classification between three cerebellar diseases and controls in a database of cerebellar ataxia patients. For reproducible comparison, promising results are presented on publicly available 2D datasets, including the ETH-80 dataset where the method achieves 88.4% classification accuracy.
Bennett, Simon J; Benguigui, Nicolas
2016-03-01
We examined spatial estimation of accelerating objects (-8, -4, 0, +4, or +8 deg/s(2)) during occlusion (600, 1,000 ms) in a spatial prediction motion task. Multiple logistic regression indicated spatial estimation was influenced by these factors such that participants estimated objects with positive acceleration to reappear behind less often than those with negative acceleration, and particularly after the longer occlusion. Individual-participant logistic regressions indicated spatial estimation was better predicted by a first-order extrapolation of the occluded object motion based on pre-occlusion velocity rather than a second-order extrapolation that took account of object acceleration. We suggest a general principle of extrapolation is involved in prediction motion tasks whereby there is a contraction of the variable of interest (i.e., displacement in spatial prediction motion and time in temporal prediction motion). Such an approach to extrapolation could be advantageous as it would offer participants better opportunity to correct for an initial estimation error.
Stoll, R R
1968-01-01
Linear Algebra is intended to be used as a text for a one-semester course in linear algebra at the undergraduate level. The treatment of the subject will be both useful to students of mathematics and those interested primarily in applications of the theory. The major prerequisite for mastering the material is the readiness of the student to reason abstractly. Specifically, this calls for an understanding of the fact that axioms are assumptions and that theorems are logical consequences of one or more axioms. Familiarity with calculus and linear differential equations is required for understand
Linear Algebra and Linear Models
Indian Academy of Sciences (India)
This monograph provides an introduction to the basic aspects of the theory oflinear estima- tion and that of testing linear hypotheses. The primary objective is to provide a basic knowledge of analysis of linear models to advanced undergraduate or first year Master's students. The second edition virtually covers the same ...
Ladefoged, Claes N.; Benoit, Didier; Law, Ian; Holm, Søren; Kjær, Andreas; Højgaard, Liselotte; Hansen, Adam E.; Andersen, Flemming L.
2015-10-01
The reconstruction of PET brain data in a PET/MR hybrid scanner is challenging in the absence of transmission sources, where MR images are used for MR-based attenuation correction (MR-AC). The main challenge of MR-AC is to separate bone and air, as neither have a signal in traditional MR images, and to assign the correct linear attenuation coefficient to bone. The ultra-short echo time (UTE) MR sequence was proposed as a basis for MR-AC as this sequence shows a small signal in bone. The purpose of this study was to develop a new clinically feasible MR-AC method with patient specific continuous-valued linear attenuation coefficients in bone that provides accurate reconstructed PET image data. A total of 164 [18F]FDG PET/MR patients were included in this study, of which 10 were used for training. MR-AC was based on either standard CT (reference), UTE or our method (RESOLUTE). The reconstructed PET images were evaluated in the whole brain, as well as regionally in the brain using a ROI-based analysis. Our method segments air, brain, cerebral spinal fluid, and soft tissue voxels on the unprocessed UTE TE images, and uses a mapping of R2* values to CT Hounsfield Units (HU) to measure the density in bone voxels. The average error of our method in the brain was 0.1% and less than 1.2% in any region of the brain. On average 95% of the brain was within ±10% of PETCT, compared to 72% when using UTE. The proposed method is clinically feasible, reducing both the global and local errors on the reconstructed PET images, as well as limiting the number and extent of the outliers.
Zheng, Youqi; Choi, Sooyoung; Lee, Deokjung
2017-12-01
A new approach based on the method of characteristics (MOC) is proposed to solve the neutron transport equation. A new three-dimensional (3D) spatial discretization is applied to avoid the instability issue of the transverse leakage iteration of the traditional 2D/1D approach. In this new approach, the axial and radial variables are discretized in two different ways: the linear expansion is performed in the axial direction, then, the 3D solution of the angular flux is transformed to be the planar solution of 2D angular expansion moments, which are solved by the planar MOC sweeping. Based on the boundary and interface continuity conditions, the 2D expansion moment solution is equivalently transformed to be the solution of the axially averaged angular flux. Using the piecewise averaged angular flux at the top and bottom surfaces of 3D meshes, the planes are coupled to give the 3D angular flux distribution. The 3D CMFD linear system is established from the surface net current of every 3D pin-mesh to accelerate the convergence of power iteration. The STREAM code is extended to be capable of handling 3D problems based on the new approach. Several benchmarks are tested to verify its feasibility and accuracy, including the 3D homogeneous benchmarks and heterogeneous benchmarks. The computational sensitivity is discussed. The results show good accuracy in all tests. With the CMFD acceleration, the convergence is stable. In addition, a pin-cell problem with void gap is calculated. This shows the advantage compared to the traditional 2D/1D MOC methods.
Burant, Aniela; Thompson, Christopher; Lowry, Gregory V; Karamalidis, Athanasios K
2016-05-17
Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch-reactor system with dual spectroscopic detectors: a near-infrared spectrometer for measuring the organic analyte in the CO2 phase and a UV detector for quantifying the analyte in the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly parameter linear free-energy relationship and to develop five new linear free-energy relationships for predicting water-sc-CO2 partitioning coefficients. A total of four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than does the model built for the entire data set.
Lion, Alexander; Mittermeier, Christoph; Johlitz, Michael
2017-09-01
A novel approach to represent the glass transition is proposed. It is based on a physically motivated extension of the linear viscoelastic Poynting-Thomson model. In addition to a temperature-dependent damping element and two linear springs, two thermal strain elements are introduced. In order to take the process dependence of the specific heat into account and to model its characteristic behaviour below and above the glass transition, the Helmholtz free energy contains an additional contribution which depends on the temperature history and on the current temperature. The model describes the process-dependent volumetric and caloric behaviour of glass-forming materials, and defines a functional relationship between pressure, volumetric strain, and temperature. If a model for the isochoric part of the material behaviour is already available, for example a model of finite viscoelasticity, the caloric and volumetric behaviour can be represented with the current approach. The proposed model allows computing the isobaric and isochoric heat capacities in closed form. The difference c_p -c_v is process-dependent and tends towards the classical expression in the glassy and equilibrium ranges. Simulations and theoretical studies demonstrate the physical significance of the model.
Dekkers, Ilona A; Roos, Rick; van der Molen, Aart J
2018-04-01
The Pharmacovigilance Risk Assessment Committee (PRAC) of the European Medicines Agency (EMA) earlier this year recommended to suspend some marketing authorisations for Gadolinium Containing Contrast Agents (GCCAs) based on linear chelators due to the potential risk of gadolinium retention in the human body. These recommendations have recently been re-evaluated by EMA's Committee for Medicinal Products for Human Use (CHMP), and confirmed the final opinion of the European Medicines Agency. This editorial provides an overview of the available GCCAs and summarises the recent evidence of gadolinium retention. Moreover, a critical appraisal of the strengths and limitations of the scientific evidence currently available on gadolinium retention is given. • EMA recommended suspension of some EU marketing authorisations of four linear GCCAs. • Brain MRI findings indicating gadolinium retention have been confirmed by mass spectrometry. • Current scientific evidence for gadolinium retention has several methodological limitations. • No clear clinical evidence exists indicating that gadolinium retention causes neurotoxicity. • Long-term safety of GCCAs, however, remains unclear.
Directory of Open Access Journals (Sweden)
Ning Ding
Full Text Available The debate on the causal association between vitamin D status, measured as serum concentration of 25-hydroxyvitamin D (25[OH]D, and various health outcomes warrants investigation in large-scale health surveys. Measuring the 25(OHD concentration for each participant is not always feasible, because of the logistics of blood collection and the costs of vitamin D testing. To address this problem, past research has used predicted 25(OHD concentration, based on multivariable linear regression, as a proxy for unmeasured vitamin D status. We restate this approach in a mathematical framework, to deduce its possible pitfalls. Monte Carlo simulation and real data from the National Health and Nutrition Examination Survey 2005-06 are used to confirm the deductions. The results indicate that variables that are used in the prediction model (for 25[OH]D concentration but not in the model for the health outcome (called instrumental variables, play an essential role in the identification of an effect. Such variables should be unrelated to the health outcome other than through vitamin D; otherwise the estimate of interest will be biased. The approach of predicted 25(OHD concentration derived from multivariable linear regression may be valid. However, careful verification that the instrumental variables are unrelated to the health outcome is required.
Zhang, Han-Ming; Wang, Lin-Yuan; Yan, Bin; Li, Lei; Xi, Xiao-Qi; Lu, Li-Zhong
2013-07-01
Linear scan computed tomography (LCT) is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation (TV) minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method (ADM) to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.
Wan, Lihong; Liu, Na; Guo, Yiyou; Huo, Hong; Fang, Tao
2017-01-01
We propose a local feature representation based on two types of linear filtering, feature pooling, and nonlinear divisive normalization for remote sensing image classification. First, images are decomposed using a bank of log-Gabor and Gaussian derivative filters to obtain filtering responses that are robust to changes in various lighting conditions. Second, the filtering responses computed using the same filter at nearby locations are pooled together to enhance position invariance and compact representation. Third, divisive normalization with channel-wise strategy, in which each pooled feature is divided by a common factor plus the sum of the neighboring features to reduce dependencies among nearby locations, is introduced to extract divisive normalization features (DNFs). Power-law transformation and principal component analysis are applied to make DNF significantly distinguishable, followed by feature fusion to enhance local description. Finally, feature encoding is used to aggregate DNFs into a global representation. Experiments on 21-class land use and 19-class satellite scene datasets demonstrate the effectiveness of the channel-wise divisive normalization compared with standard normalization across channels and the fusion of the two types of linear filtering in improving classification accuracy. The experiments also illustrate that the proposed method is competitive with state-of-the-art approaches.
Acharya, U Rajendra; Sree, S Vinitha; Alvin, Ang Peng Chuan; Yanti, Ratna; Suri, Jasjit S
2012-04-01
Epilepsy, a neurological disorder, is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals, which are used to detect the presence of seizures, are non-linear and dynamic in nature. Visual inspection of the EEG signals for detection of normal, interictal, and ictal activities is a strenuous and time-consuming task due to the huge volumes of EEG segments that have to be studied. Therefore, non-linear methods are being widely used to study EEG signals for the automatic monitoring of epileptic activities. The aim of our work is to develop a Computer Aided Diagnostic (CAD) technique with minimal pre-processing steps that can classify all the three classes of EEG segments, namely normal, interictal, and ictal, using a small number of highly discriminating non-linear features in simple classifiers. To evaluate the technique, segments of normal, interictal, and ictal EEG segments (100 segments in each class) were used. Non-linear features based on the Higher Order Spectra (HOS), two entropies, namely the Approximation Entropy (ApEn) and the Sample Entropy (SampEn), and Fractal Dimension and Hurst Exponent were extracted from the segments. Significant features were selected using the ANOVA test. After evaluating the performance of six classifiers (Decision Tree, Fuzzy Sugeno Classifier, Gaussian Mixture Model, K-Nearest Neighbor, Support Vector Machine, and Radial Basis Probabilistic Neural Network) using a combination of the selected features, we found that using a set of all the selected six features in the Fuzzy classifier resulted in 99.7% classification accuracy. We have demonstrated that our technique is capable of achieving high accuracy using a small number of features that accurately capture the subtle differences in the three different types of EEG (normal, interictal, and ictal) segments. The technique can be easily written as a software application and used by medical professionals without any extensive training and cost. Such software
Linearity in Process Languages
DEFF Research Database (Denmark)
Nygaard, Mikkel; Winskel, Glynn
2002-01-01
The meaning and mathematical consequences of linearity (managing without a presumed ability to copy) are studied for a path-based model of processes which is also a model of affine-linear logic. This connection yields an affine-linear language for processes, automatically respecting open-map bisi......The meaning and mathematical consequences of linearity (managing without a presumed ability to copy) are studied for a path-based model of processes which is also a model of affine-linear logic. This connection yields an affine-linear language for processes, automatically respecting open......-map bisimulation, in which a range of process operations can be expressed. An operational semantics is provided for the tensor fragment of the language. Different ways to make assemblies of processes lead to different choices of exponential, some of which respect bisimulation....
Liesen, Jörg
2015-01-01
This self-contained textbook takes a matrix-oriented approach to linear algebra and presents a complete theory, including all details and proofs, culminating in the Jordan canonical form and its proof. Throughout the development, the applicability of the results is highlighted. Additionally, the book presents special topics from applied linear algebra including matrix functions, the singular value decomposition, the Kronecker product and linear matrix equations. The matrix-oriented approach to linear algebra leads to a better intuition and a deeper understanding of the abstract concepts, and therefore simplifies their use in real world applications. Some of these applications are presented in detailed examples. In several ‘MATLAB-Minutes’ students can comprehend the concepts and results using computational experiments. Necessary basics for the use of MATLAB are presented in a short introduction. Students can also actively work with the material and practice their mathematical skills in more than 300 exerc...
Searle, Shayle R
2012-01-01
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
Solow, Daniel
2014-01-01
This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.
Berberian, Sterling K
2014-01-01
Introductory treatment covers basic theory of vector spaces and linear maps - dimension, determinants, eigenvalues, and eigenvectors - plus more advanced topics such as the study of canonical forms for matrices. 1992 edition.
Christofilos, N.C.; Polk, I.J.
1959-02-17
Improvements in linear particle accelerators are described. A drift tube system for a linear ion accelerator reduces gap capacity between adjacent drift tube ends. This is accomplished by reducing the ratio of the diameter of the drift tube to the diameter of the resonant cavity. Concentration of magnetic field intensity at the longitudinal midpoint of the external sunface of each drift tube is reduced by increasing the external drift tube diameter at the longitudinal center region.
Directory of Open Access Journals (Sweden)
Hao Zha
2016-01-01
Full Text Available The baseline design of CLIC (Compact Linear Collider uses X-band accelerating structures for its main linacs. In order to maintain beam stability in multibunch operation, long-range transverse wakefields must be suppressed by 2 orders of magnitude between successive bunches, which are separated in time by 0.5 ns. Such strong wakefield suppression is achieved by equipping every accelerating structure cell with four damping waveguides terminated with individual rf loads. A beam-based experiment to directly measure the effectiveness of this long-range transverse wakefield and benchmark simulations was made in the FACET test facility at SLAC using a prototype CLIC accelerating structure. The experiment showed good agreement with the simulations and a strong suppression of the wakefields with an unprecedented minimum resolution of 0.1 V/(pC mm m.
Pekkanen, Jami; Lappi, Otto
2017-12-18
We introduce a conceptually novel method for eye-movement signal analysis. The method is general in that it does not place severe restrictions on sampling frequency, measurement noise or subject behavior. Event identification is based on segmentation that simultaneously denoises the signal and determines event boundaries. The full gaze position time-series is segmented into an approximately optimal piecewise linear function in O(n) time. Gaze feature parameters for classification into fixations, saccades, smooth pursuits and post-saccadic oscillations are derived from human labeling in a data-driven manner. The range of oculomotor events identified and the powerful denoising performance make the method useable for both low-noise controlled laboratory settings and high-noise complex field experiments. This is desirable for harmonizing the gaze behavior (in the wild) and oculomotor event identification (in the laboratory) approaches to eye movement behavior. Denoising and classification performance are assessed using multiple datasets. Full open source implementation is included.
Directory of Open Access Journals (Sweden)
Eduardo Giraldo
2013-06-01
Full Text Available In this research article a dynamic estimation of neuronal activity and brain dynamics from electroencephalographic (EEG signals is presented using a dual Kalman filter. The dynamic model for brain behavior is evaluated using physiological-based linear models. Filter performance is analyzed for simulated and clinical EEG data, over several noise conditions. As a result a better performance on the solution of the dynamic inverse problem is achieved, in case of time varying parameters compared with the system with fixed parameters and the static case. An evaluation of computational load is performed when predicted dynamic cases, estimated using the Kalman filter, are up to ten times faster than the static case.
Bao, Qian; Han, Kuoye; Lin, Yun; Zhang, Bingchen; Liu, Jianguo; Hong, Wen
2016-01-01
We propose an imaging algorithm for downward-looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) in the circumstance of cross-track sparse and nonuniform array configuration. Considering the off-grid effect and the resolution improvement, the algorithm combines pseudo-polar formatting algorithm, reweighed atomic norm minimization (RANM), and a parametric relaxation-based cyclic approach (RELAX) to improve the imaging performance with a reduced number of array antennas. RANM is employed in the cross-track imaging after pseudo-polar formatting the DLSLA 3-D SAR echo signal, then the reconstructed results are refined by RELAX. By taking advantage of the reweighted scheme, RANM can improve the resolution of the atomic norm minimization, and outperforms discretized compressive sensing schemes that suffer from off-grid effect. The simulated and real data experiments of DLSLA 3-D SAR verify the performance of the proposed algorithm.
Wang, Ping; Zha, Hao; Syratchev, Igor; Shi, Jiaru; Chen, Huaibi
2017-11-01
We present an X-band high-power pulse compression system for a klystron-based compact linear collider. In this system design, one rf power unit comprises two klystrons, a correction cavity chain, and two SLAC Energy Doubler (SLED)-type X-band pulse compressors (SLEDX). An rf pulse passes the correction cavity chain, by which the pulse shape is modified. The rf pulse is then equally split into two ways, each deploying a SLEDX to compress the rf power. Each SLEDX produces a short pulse with a length of 244 ns and a peak power of 217 MW to power four accelerating structures. With the help of phase-to-amplitude modulation, the pulse has a dedicated shape to compensate for the beam loading effect in accelerating structures. The layout of this system and the rf design and parameters of the new pulse compressor are described in this work.
Laser-based linear and nonlinear guided elastic waves at surfaces (2D) and wedges (1D).
Hess, Peter; Lomonosov, Alexey M; Mayer, Andreas P
2014-01-01
The characteristic features and applications of linear and nonlinear guided elastic waves propagating along surfaces (2D) and wedges (1D) are discussed. Laser-based excitation, detection, or contact-free analysis of these guided waves with pump-probe methods are reviewed. Determination of material parameters by broadband surface acoustic waves (SAWs) and other applications in nondestructive evaluation (NDE) are considered. The realization of nonlinear SAWs in the form of solitary waves and as shock waves, used for the determination of the fracture strength, is described. The unique properties of dispersion-free wedge waves (WWs) propagating along homogeneous wedges and of dispersive wedge waves observed in the presence of wedge modifications such as tip truncation or coatings are outlined. Theoretical and experimental results on nonlinear wedge waves in isotropic and anisotropic solids are presented. Copyright © 2013 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Oh, S.-D. [Hyosung Corp., Seoul (Korea, Republic of)]. E-mail: ohsidk@hyosung.com; Kwak, H.-Y. [Chung-Ang Univ., Mechanical Engineering Dept., Seoul (Korea, Republic of)]. E-mail: kwakhy@cau.ac.kr
2005-07-01
An optimal planning for gas turbine cogeneration system has been studied. The planning problem considered in this study is to determine the optimal configuration of the system equipments and optimal operational policy of the system when the annual energy demands of electric power, heat and cooling are given a priori. The main benefit of the optimal planning is to minimize operational costs and to save energy by efficient energy utilization. A mixed-integer linear programming and the branch and bound algorithm have been adopted to obtain the optimal solution. Both the optimal configuration of the system equipments and the optimal operation policy has been obtained based on annual cost method. The planning method employed here may be applied to the planning problem of the cogeneration plant to any specific building or hotel. (author)
Directory of Open Access Journals (Sweden)
Stojanović Zdenka M.
2007-01-01
Full Text Available Background/Aim. In malocclusion of skeletal class III, mandible is located in front of maxilla in sagital plain, which is manifested by a lower value of the sagital inter-jaw angle than in skeletal class I, where the jaw sagital relation is normal. Apart from the deformities on mandible and/or maxilla, in skeletal class III deformities are also frequent on the cranial base. The aim of this research was to find the differences in the parameter values on the cranial base among the children with skeletal class III and the children with skeletal class I in the period of mixed dentition. Methods. After clinical examination and orthopan-tomography, profile radiography of the head was analyzed in 60 examinees, aged from 6−12 years. The examinees were divided into two groups: group 1 - the children with skeletal class III; group 2 - the children with skeletal class I. Both linear and angular parameters on the cranial base were measured, as well as the angles of maxillary and mandible prognatism and the angle of sagital inter-jaw relation. The level of difference in the parameter values between the groups was estimated and the degree of correlation of the main angle of the cranial base with the angles of sagital position of the jaws in each of the two groups was established. Results. A significant difference between the groups was found only in the average values of the angles of maxillary prognatism and sagital interjaw relation. In the group 1, the main angle of the cranial base was in a significant correlation with the angles of sagital positions of the jaws, while in the group 2, such significance was not found. Conclusion. There were no significant differences in the parameter values on the cranial base between the groups. There was a significant correlation of the main angle of the cranial base with the angles of sagital position of the jaws in the group 1 only. .
Directory of Open Access Journals (Sweden)
Børresen-Dale Anne-Lise
2002-10-01
Full Text Available Abstract Background T7 based linear amplification of RNA is used to obtain sufficient antisense RNA for microarray expression profiling. We optimized and systematically evaluated the fidelity and reproducibility of different amplification protocols using total RNA obtained from primary human breast carcinomas and high-density cDNA microarrays. Results Using an optimized protocol, the average correlation coefficient of gene expression of 11,123 cDNA clones between amplified and unamplified samples is 0.82 (0.85 when a virtual array was created using repeatedly amplified samples to minimize experimental variation. Less than 4% of genes show changes in expression level by 2-fold or greater after amplification compared to unamplified samples. Most changes due to amplification are not systematic both within one tumor sample and between different tumors. Amplification appears to dampen the variation of gene expression for some genes when compared to unamplified poly(A+ RNA. The reproducibility between repeatedly amplified samples is 0.97 when performed on the same day, but drops to 0.90 when performed weeks apart. The fidelity and reproducibility of amplification is not affected by decreasing the amount of input total RNA in the 0.3–3 micrograms range. Adding template-switching primer, DNA ligase, or column purification of double-stranded cDNA does not improve the fidelity of amplification. The correlation coefficient between amplified and unamplified samples is higher when total RNA is used as template for both experimental and reference RNA amplification. Conclusion T7 based linear amplification reproducibly generates amplified RNA that closely approximates original sample for gene expression profiling using cDNA microarrays.
Directory of Open Access Journals (Sweden)
Yu-E Song
2014-01-01
Full Text Available The Wigner-Ville distribution (WVD based on the linear canonical transform (LCT (WDL not only has the advantages of the LCT but also has the good properties of WVD. In this paper, some new and important properties of the WDL are derived, and the relationships between WDL and some other time-frequency distributions are discussed, such as the ambiguity function based on LCT (LCTAF, the short-time Fourier transform (STFT, and the wavelet transform (WT. The WDLs of some signals are also deduced. A novel definition of the WVD based on the LCT and generalized instantaneous autocorrelation function (GWDL is proposed and its applications in the estimation of parameters for QFM signals are also discussed. The GWDL of the QFM signal generates an impulse and the third-order phase coefficient of QFM signal can be estimated in accordance with the position information of such impulse. The proposed algorithm is fast because it only requires 1-dimensional maximization. Also the new algorithm only has fourth-order nonlinearity thus it has accurate estimation and low signal-to-noise ratio (SNR threshold. The simulation results are provided to support the theoretical results.
Wang, Xingjian; Liao, Rui; Shi, Cun; Wang, Shaoping
2017-10-25
Moving towards the more electric aircraft (MEA), a hybrid actuator configuration provides an opportunity to introduce electromechanical actuator (EMA) into primary flight control. In the hybrid actuation system (HAS), an electro-hydraulic servo actuator (EHSA) and an EMA operate on the same control surface. In order to solve force fighting problem in HAS, this paper proposes a novel linear extended state observer (LESO)-based motion synchronization control method. To cope with the problem of unavailability of the state signals required by the motion synchronization controller, LESO is designed for EHSA and EMA to observe the state variables. Based on the observed states of LESO, motion synchronization controllers could enable EHSA and EMA to simultaneously track the desired motion trajectories. Additionally, nonlinearities, uncertainties and unknown disturbances as well as the coupling term between EHSA and EMA can be estimated and compensated by using the extended state of the proposed LESO. Finally, comparative simulation results indicate that the proposed LESO-based motion synchronization controller could reduce significant force fighting between EHSA and EMA.
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
Sahai, Vivek
2013-01-01
Beginning with the basic concepts of vector spaces such as linear independence, basis and dimension, quotient space, linear transformation and duality with an exposition of the theory of linear operators on a finite dimensional vector space, this book includes the concept of eigenvalues and eigenvectors, diagonalization, triangulation and Jordan and rational canonical forms. Inner product spaces which cover finite dimensional spectral theory and an elementary theory of bilinear forms are also discussed. This new edition of the book incorporates the rich feedback of its readers. We have added new subject matter in the text to make the book more comprehensive. Many new examples have been discussed to illustrate the text. More exercises have been included. We have taken care to arrange the exercises in increasing order of difficulty. There is now a new section of hints for almost all exercises, except those which are straightforward, to enhance their importance for individual study and for classroom use.
Edwards, Harold M
1995-01-01
In his new undergraduate textbook, Harold M Edwards proposes a radically new and thoroughly algorithmic approach to linear algebra Originally inspired by the constructive philosophy of mathematics championed in the 19th century by Leopold Kronecker, the approach is well suited to students in the computer-dominated late 20th century Each proof is an algorithm described in English that can be translated into the computer language the class is using and put to work solving problems and generating new examples, making the study of linear algebra a truly interactive experience Designed for a one-semester course, this text adopts an algorithmic approach to linear algebra giving the student many examples to work through and copious exercises to test their skills and extend their knowledge of the subject Students at all levels will find much interactive instruction in this text while teachers will find stimulating examples and methods of approach to the subject
Allenby, Reg
1995-01-01
As the basis of equations (and therefore problem-solving), linear algebra is the most widely taught sub-division of pure mathematics. Dr Allenby has used his experience of teaching linear algebra to write a lively book on the subject that includes historical information about the founders of the subject as well as giving a basic introduction to the mathematics undergraduate. The whole text has been written in a connected way with ideas introduced as they occur naturally. As with the other books in the series, there are many worked examples.Solutions to the exercises are available onlin
Abdelaziz, Osama S; Kandil, Alaa; El-Assaal, Shaaban; Abdelaziz, Amro; Rostom, Yosry; Rashed, Yaser
2011-01-01
Meningiomas are mostly benign but some are atypical or malignant. Surgical resection is curative when complete removal of benign meningiomas is contemplated. Incompletely excised and recurrent tumors are frequently treated with fractionated radiation therapy or stereotactic radiosurgery. The purpose of this study is to evaluate the short-term radiological and functional outcomes of a single center using linear accelerator (Linac) stereotactic radiosurgery for the treatment of intracranial meningiomas. Twenty-nine patients (12 males and 17 females) with 30 meningiomas, in different brain locations (skull base and non-skull base meningiomas), were treated with Linac-based stereotactic radiosurgery. The mean tumor volume was 6.3 cm³, and the mean tumor marginal and maximum doses were 10.9 and 15 Gy, respectively. The median prescribed isodose line was 80%. The patients were followed-up for a minimum of 3 years. Regarding radiological outcome, nine (30%) meningiomas demonstrated evident volume reduction, 19 (63.3%) meningiomas remained unchanged, and two (6.7%) meningiomas increased in size after radiosurgery. The local tumor control rates for skull base meningiomas and non-skull base meningiomas after radiosurgery were 90.9% and 100%, respectively. Regarding functional outcomes, 64% of patients presenting with cranial neuropathies showed improvement of their cranial nerve functions and 29% of patients remained unchanged. One patient had temporary trigeminal neuropathy. Although radiosurgery for meningiomas is generally effective and quite safe in achieving high control rates with minimum morbidity over short- and intermediate-term periods of follow-up, tumor progression might occur in a delayed manner after initial apparent control for few years. We recommend continued follow-up for longer periods to better assess the long-term outcomes.
Carvajal, Gonzalo; Figueroa, Miguel
2014-07-01
Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights
Galasso, Matteo; Fabbri, Andrea; Borrazzo, Cristian; Cencelli, Valentino Orsolini; Pani, Roberto
2016-06-01
In this work, we developed a model that is able to predict in a few seconds the response of a gamma camera based on continuous scintillator in terms of linearity and spatial resolution in the whole field of view (FoV). This model will be useful during the design phase of a SPECT or PET detector in order to predict and optimize gamma camera performance by varying the parameter values of its components (scintillator, light guides, and photodetector). Starting from a model of the scintillation light distribution on the photodetector sensitive surface, a theoretical analysis based on the estimation theory is carried out in order to find the analytical expressions of bias and FWHM related to four interaction position estimation methods: the classical Center of Gravity method (Anger Logic), an enhanced Center of Gravity method, a Mean Square Error fitting method, and the Maximum Likelihood Estimation method. Afterwards, spatial resolution as well as depth of interaction (DOI) distribution effects are evaluated by processing biases and FWHMs at different DOIs. The comparison between the model and GEANT4 Monte Carlo simulations of four different detection systems has been carried out. Our model prediction errors of spatial resolution, in terms of percentage RMSDs with respect to the simulated spatial resolution, are lower than 13.2% in the whole FoV for three estimation methods. The computational time to calculate spatial resolutions with the model in the whole FoV is five order of magnitudes faster than an equivalent standard Monte Carlo simulation.
Ptaszek, Paweł; Zmudziński, Daniel; Kruk, Joanna; Kaczmarczyk, Kacper; Rożnowski, Wojciech; Berski, Wiktor
2014-01-01
The aim of this work was to evaluate the physicochemical properties of fresh foams based on egg white proteins, xanthan gum and gum Arabic. The distributions of the size of gas bubbles suspended in liquid were determined, as well as density and volume fraction of gas phase of the generated foams. Additionally, the viscoelastic properties in the linear range were measured, and the results were analyzed with the use of the fractional Zener model. It was shown, that foam supplementation with hydrocolloids considerably decreased their volume fraction of gas phase in comparison to pure egg white protein-based foams. Application of gum Arabic did not cause an increase in the size of foam bubbles when compared to pure white egg foam, whereas application of xanthan gum significantly decreased the size of the bubbles. Application of the fractional Zener model allowed to determine the relaxation times, their intensity in analyzed suspensions and also equilibrium module (Ge ). The increase in the concentration of xanthan gum resulted in the prolongation of the relaxation time and increased its intensity. Gum Arabic, when added, weakened the viscoelastic properties of the mixture as a viscoelastic solid.
Jeong, Gu-Min; Nghia, Nguyen Trong; Choi, Sang-Il
2015-01-01
In this paper, we present a pseudo optimization method for electronic nose (e-nose) data using region selection with feature feedback based on regularized linear discriminant analysis (R-LDA) to enhance the performance and cost functions of an e-nose system. To implement cost- and performance-effective e-nose systems, the number of channels, sampling time and sensing time of the e-nose must be considered. We propose a method to select both important channels and an important time-horizon by analyzing e-nose sensor data. By extending previous feature feedback results, we obtain a two-dimensional discriminant information map consisting of channels and time units by reverse mapping the feature space to the data space based on R-LDA. The discriminant information map enables optimal channels and time units to be heuristically selected to improve the performance and cost functions. The efficacy of the proposed method is demonstrated experimentally for different volatile organic compounds. In particular, our method is both cost and performance effective for the real implementation of e-nose systems. PMID:25559000
Li, Chung-I; Shyr, Yu
2016-12-01
As RNA-seq rapidly develops and costs continually decrease, the quantity and frequency of samples being sequenced will grow exponentially. With proteomic investigations becoming more multivariate and quantitative, determining a study's optimal sample size is now a vital step in experimental design. Current methods for calculating a study's required sample size are mostly based on the hypothesis testing framework, which assumes each gene count can be modeled through Poisson or negative binomial distributions; however, these methods are limited when it comes to accommodating covariates. To address this limitation, we propose an estimating procedure based on the generalized linear model. This easy-to-use method constructs a representative exemplary dataset and estimates the conditional power, all without requiring complicated mathematical approximations or formulas. Even more attractive, the downstream analysis can be performed with current R/Bioconductor packages. To demonstrate the practicability and efficiency of this method, we apply it to three real-world studies, and introduce our on-line calculator developed to determine the optimal sample size for a RNA-seq study.
Camilo, Daniela Castro
2017-08-30
Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.
Wihardi, Y.; Setiawan, W.; Nugraha, E.
2018-01-01
On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.
Nakhanu, Shikuku Beatrice; Musasia, Amadalo Maurice
2015-01-01
The topic Linear Programming is included in the compulsory Kenyan secondary school mathematics curriculum at form four. The topic provides skills for determining best outcomes in a given mathematical model involving some linear relationship. This technique has found application in business, economics as well as various engineering fields. Yet many…
Zhu, Dan; Chen, Jian; Pan, Shilong
2016-05-16
A multi-octave highly-linear analog photonic link with simultaneous suppression of second-order intermodulation distortion (IMD2) and third-order intermodulation distortion (IMD3) is proposed and demonstrated based on a single integrated polarization-multiplexing dual-parallel Mach-Zehnder modulator (PM-DPMZM). The IMD2 is eliminated by biasing one sub-MZM in each sub-DPMZM at a point close to the maximum transmission point and the other sub-MZM at a point close to the minimum transmission point. The obtained fundamental frequency terms are in phase while the second-order harmonics are complementary when the two outputs of the two sub-MZMs are photodetected. The IMD3 is suppressed by adjusting the RF powers introduced to the two sub-DPMZMs, producing two complementary IMD3 terms when the modulated signals are photodetected. An experiment is carried out. Simultaneous suppression of IMD2 and IMD3 is achieved. The second-order spurious-free dynamic range (SFDR2) and third-order spurious-free dynamic range (SFDR3) are 82 dB·Hz1/2 and 110 dB·Hz2/3, respectively, indicating an improvement of 12 dB in SFDR2 and 13 dB in SFDR3 as compared with the low-biased MZM based analog photonic link, or an improvement of 3 dB in SFDR2 and 16 dB in SFDR3 as compared with the quadrature-biased MZM based photonic link.
Karloff, Howard
1991-01-01
To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...
Pérez Maciel, M.; Montenegro Orenday, J. A.; Estudillo Ayala, J. M.; Jáuregui-Vázquez, D.; Sierra-Hernandez, J. M.; Hernandez-Garcia, J. C.; Rojas-Laguna, R.
2016-09-01
Tunable wavelength erbium doped fiber linear cavity laser, based on mechanically induced long-period fiber gratings (MLPFG) is presented. The laser was tuned applying pressure over the MLPFG, in order to monitor this, pressure is applied over a plate with periodic grooves that has a short length, this pressure is controlled by a digital torque tester as a result tunable effect is observed. The grooves have a period of 620µm and the maximal pressure without breakpoint fiber is around 0.80lb-in2. Furthermore, the MLPFG used can be erased, reconfigured and exhibit a transmission spectra with termal stability, similar to high cost photoinduced long period gratings. In this work, by pressure increment distributed over the MLPFG from 0.40 lb-in2 to 0. 70 lb-in 2, tuned operation range of 14nm was observed and single line emission was tuned in the C telecommunication band. According to the stability analysis the signal to noise ratio was 29 dB and minimal wavelength oscillations of 0.29nm.
Directory of Open Access Journals (Sweden)
Amir R. Ali
2017-01-01
Full Text Available This paper presents and verifies the mathematical model of an electric field senor based on the whispering gallery mode (WGM. The sensing element is a dielectric microsphere, where the light is used to tune the optical modes of the microsphere. The light undergoes total internal reflection along the circumference of the sphere; then it experiences optical resonance. The WGM are monitored as sharp dips on the transmission spectrum. These modes are very sensitive to morphology changes of the sphere, such that, for every minute change in the sphere’s morphology, a shift in the transmission spectrum will happen and that is known as WGM shifts. Due to the electrostriction effect, the applied electric field will induce forces acting on the surface of the dielectric sphere. In turn, these forces will deform the sphere causing shifts in its WGM spectrum. The applied electric field can be obtained by calculating these shifts. Navier’s equation for linear elasticity is used to model the deformation of the sphere to find the WGM shift. The finite element numerical studies are performed to verify the introduced model and to study the behavior of the sensor at different values of microspheres’ Young’s modulus and dielectric constant. Furthermore, the sensitivity and resolution of the developed WGM electric filed sensor model will be presented in this paper.
Directory of Open Access Journals (Sweden)
S. Mohammad Arabzad
2012-06-01
Full Text Available In recent years, numerous methods have been proposed to deal with supplier evaluation and selection problem, but a point which has been usually neglected by researchers is the role of purchasing items. The aim of this paper is to propose an integrated approach to select suppliers and allocate orders on the basis of the nature of the purchasing items which means that this issue plays an important role in supplier selection and order allocation. Therefore, items are first categorized according to the Kraljic’s model by the use of FMEA technique. Then, suppliers are categorized and evaluated in four phases with respect to different types of purchasing items (Strategic, Bottleneck, Leverage and Routine. Finally, an integer linear programming is utilized to allocate purchasing orders to suppliers. Furthermore, an empirical example is conducted to illustrate the stage of proposed approach. Results imply that ranking of suppliers and allocation of purchasing items based on the nature of purchasing items will create more capabilities in managing purchasing items and suppliers .
Wu, Z.; Gao, K.; Wang, Z. L.; Shao, Q. G.; Hu, R. F.; Wei, C. X.; Zan, G. B.; Wali, F.; Luo, R. H.; Zhu, P. P.; Tian, Y. C.
2017-06-01
In X-ray grating-based phase contrast imaging, information retrieval is necessary for quantitative research, especially for phase tomography. However, numerous and repetitive processes have to be performed for tomographic reconstruction. In this paper, we report a novel information retrieval method, which enables retrieving phase and absorption information by means of a linear combination of two mutually conjugate images. Thanks to the distributive law of the multiplication as well as the commutative law and associative law of the addition, the information retrieval can be performed after tomographic reconstruction, thus simplifying the information retrieval procedure dramatically. The theoretical model of this method is established in both parallel beam geometry for Talbot interferometer and fan beam geometry for Talbot-Lau interferometer. Numerical experiments are also performed to confirm the feasibility and validity of the proposed method. In addition, we discuss its possibility in cone beam geometry and its advantages compared with other methods. Moreover, this method can also be employed in other differential phase contrast imaging methods, such as diffraction enhanced imaging, non-interferometric imaging, and edge illumination.
Directory of Open Access Journals (Sweden)
Seokbin Lim
2012-01-01
Full Text Available Birkhoff theory exhibits an analytical steady state liner collapse model of shaped charges followed by jetting process. It also provides the fundamental idea in study of shaped charges and has widened its application in many areas, including a configuration where the detonation front strikes the entire liner surface at the same time providing the α = β (liner apex angle α, and the liner collapse point angle β condition in the literature. Upon consideration of the detonation front propagation along the lateral length of the core charge in LSCs (linear shaped charges, a further modification of the Birkhoff theory motivated by the unique geometrical condition of LSCs and the α = β condition is necessary to correctly describe the jetting behavior of LSCs which is different than that of CSCs (conical shaped charges. Based on such unique geometrical properties of LSCs, the original Birkhoff theory was modified and an analytical steady state LSCs model was built. The analytical model was then compared to the numerical simulation results created from Autodyn™ in terms of M/C ratio and apex angles in three different sized LSCs, and it exhibits favorable results in a limited range.
Ye, Dan; Chen, Mengmeng; Li, Kui
2017-06-22
In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Lee, Taesam; Ouarda, Taha B. M. J.; Yoon, Sunkwon
2017-11-01
Climate change frequently causes highly nonlinear and irregular behaviors in hydroclimatic systems. The stochastic simulation of hydroclimatic variables reproduces such irregular behaviors and is beneficial for assessing their impact on other regimes. The objective of the current study is to propose a novel method, a k-nearest neighbor (KNN) based on the local linear regression method (KLR), to reproduce nonlinear and heteroscedastic relations in hydroclimatic variables. The proposed model was validated with a nonlinear, heteroscedastic, lag-1 time dependent test function. The validation results of the test function show that the key statistics, nonlinear dependence, and heteroscedascity of the test data are reproduced well by the KLR model. In contrast, a traditional resampling technique, KNN resampling (KNNR), shows some biases with respect to key statistics, such as the variance and lag-1 correlation. Furthermore, the proposed KLR model was used to simulate the annual minimum of the consecutive 7-day average daily mean flow (Min7D) of the Romaine River, Quebec. The observed and extended North Atlantic Oscillation (NAO) index is incorporated into the model. The case study results of the observed period illustrate that the KLR model sufficiently reproduced key statistics and the nonlinear heteroscedasticity relation. For the future period, a lower mean is observed, which indicates that drier conditions other than normal might be expected in the next decade in the Romaine River. Overall, it is concluded that the KLR model can be a good alternative for simulating irregular and nonlinear behaviors in hydroclimatic variables.
Zhang, Jun; Guo, Yu-Feng; Xu, Yue; Lin, Hong; Yang, Hui; Hong, Yang; Yao, Jia-Fei
2015-02-01
A novel one-dimensional (1D) analytical model is proposed for quantifying the breakdown voltage of a reduced surface field (RESURF) lateral power device fabricated on silicon on an insulator (SOI) substrate. We assume that the charges in the depletion region contribute to the lateral PN junctions along the diagonal of the area shared by the lateral and vertical depletion regions. Based on the assumption, the lateral PN junction behaves as a linearly graded junction, thus resulting in a reduced surface electric field and high breakdown voltage. Using the proposed model, the breakdown voltage as a function of device parameters is investigated and compared with the numerical simulation by the TCAD tools. The analytical results are shown to be in fair agreement with the numerical results. Finally, a new RESURF criterion is derived which offers a useful scheme to optimize the structure parameters. This simple 1D model provides a clear physical insight into the RESURF effect and a new explanation on the improvement in breakdown voltage in an SOI RESURF device. Project supported by the National Natural Science Foundation of China (Grant No. 61076073) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20133223110003).
Ren, Zhong; Huang, Shuanggen; Liu, Guodong; Huang, Zhen; Zeng, Lvming
2011-06-01
Since the water resource is being seriously polluted with the development of the human society, the monitoring of the available water resource is an impending task. The concentration of the dissolved organic matter, oxygen and inorganic salt in water can be checked by means of some methods, e.g. electrolysis, electrochemical method, colorimetry. But because some drawbacks are existed in these methods, the laser-induced fluorescence (LIF) spectrophotometry method is adopted into this paper. And a novel LIF spectrophotometer for water quality monitor (WQM) is designed. In this WQM, the 3rd harmonic of the Q switched Nd:YAG laser is used as the induced fluorescence light-source. And for the splitting-light system of the spectrophotometer for WQM, in order to improve the resolution and light-passing efficiency, a novel volume holography transmissive(VHT) grating is used as the diffraction grating instead of the plane or holography grating. Meanwhile, the linear CCD with combined data acquisition (DAQ) card is used as the fluorescence spectral detection system and virtual instrument (VI) technology based on LabVIEW is used to control the spectral acquisition and analysis. Experimental results show that the spatial resolution of the novel spectrophotometer for WQM is improved, its resolution can reach 2nm. And the checking accuracy of this WQM is higher than others. Therefore, the novel LIF spectrophotometer for WQM has the potential value in the water quality monitoring and biochemical application.
Cui, Ke; Ren, Zhongjie; Li, Xiangyu; Liu, Zongkai; Zhu, Rihong
2017-01-01
Time-to-digital converters (TDCs) using dedicated carry chains of field programmable gate arrays (FPGAs) are usually organized in tapped-delay-line type which are intensively researched in recent years. However this method incurs poor differential nonlinearity (DNL) which arises from the inherent uneven bin granularity. This paper proposes a TDC architecture which utilizes the carry chains in a quite different manner in order to alleviate this long-standing problem. Two independent carry chains working as the delay lines for the fine time interpolation are organized in a ring-oscillator-based Vernier style and the time difference between them is finely adjusted by assigning different number of basic delay cells. A specific design flow is described to obtain the desired delay difference. The TDC was implemented on a Stratix III FPGA. Test results show that the obtained resolution is 31 ps and the DNL\\INL is in the range of (-0.080 LSB, 0.073 LSB)(-0.087 LSB, 0.091 LSB). This demonstrates that the proposed architecture greatly improves linearity compared to previous techniques. Additionally the resource cost is rather low which uses only 319 LUTs and 104 registers per TDC channel.
Soares Dos Santos, Marco P; Ferreira, Jorge A F; Simões, José A O; Pascoal, Ricardo; Torrão, João; Xue, Xiaozheng; Furlani, Edward P
2016-01-04
Magnetic levitation has been used to implement low-cost and maintenance-free electromagnetic energy harvesting. The ability of levitation-based harvesting systems to operate autonomously for long periods of time makes them well-suited for self-powering a broad range of technologies. In this paper, a combined theoretical and experimental study is presented of a harvester configuration that utilizes the motion of a levitated hard-magnetic element to generate electrical power. A semi-analytical, non-linear model is introduced that enables accurate and efficient analysis of energy transduction. The model predicts the transient and steady-state response of the harvester a function of its motion (amplitude and frequency) and load impedance. Very good agreement is obtained between simulation and experiment with energy errors lower than 14.15% (mean absolute percentage error of 6.02%) and cross-correlations higher than 86%. The model provides unique insight into fundamental mechanisms of energy transduction and enables the geometric optimization of harvesters prior to fabrication and the rational design of intelligent energy harvesters.
Energy Technology Data Exchange (ETDEWEB)
Ureba, A. [Dpto. Fisiología Médica y Biofísica. Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Salguero, F. J. [Nederlands Kanker Instituut, Antoni van Leeuwenhoek Ziekenhuis, 1066 CX Ámsterdam, The Nederlands (Netherlands); Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Leal, A., E-mail: alplaza@us.es [Dpto. Fisiología Médica y Biofísica, Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Miras, H. [Servicio de Radiofísica, Hospital Universitario Virgen Macarena, E-41009 Sevilla (Spain); Linares, R.; Perucha, M. [Servicio de Radiofísica, Hospital Infanta Luisa, E-41010 Sevilla (Spain)
2014-08-15
Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast
Ureba, A; Salguero, F J; Barbeiro, A R; Jimenez-Ortega, E; Baeza, J A; Miras, H; Linares, R; Perucha, M; Leal, A
2014-08-01
The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called "biophysical" map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved
Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A
2016-03-01
In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.
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Luigi Capoferri
Full Text Available Prediction of human Cytochrome P450 (CYP binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD simulations and Linear Interaction Energy (LIE theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE of 4.1 kJ mol-1 and a standard error in prediction (SDEP in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units.
Landry, Guillaume; Seco, Joao; Gaudreault, Mathieu; Verhaegen, Frank
2013-10-07
Dual energy computed tomography (DECT) can provide simultaneous estimation of relative electron density ρe and effective atomic number Zeff. The ability to obtain these quantities (ρe, Zeff) has been shown to benefit selected radiotherapy applications where tissue characterization is required. The conventional analysis method (spectral method) relies on knowledge of the CT scanner photon spectra which may be difficult to obtain accurately. Furthermore an approximate empirical attenuation correction of the photon spectrum through the patient is necessary. We present an alternative approach based on a parameterization of the measured ratio of low and high kVp linear attenuation coefficients for deriving Zeff which does not require the estimation of the CT scanner spectra. In a first approach, the tissue substitute method (TSM), the Rutherford parameterization of the linear attenuation coefficients was employed to derive a relation between Zeff and the ratio of the linear attenuation coefficients measured at the low and high kVp of the CT scanner. A phantom containing 16 tissue mimicking inserts was scanned with a dual source DECT scanner at 80 and 140 kVp. The data from the 16 inserts phantom was used to obtain model parameters for the relation between Zeff and [Formula: see text]. The accuracy of the method was evaluated with a second phantom containing 4 tissue mimicking inserts. The TSM was compared to a more complex approach, the reference tissue method (RTM), which requires the derivation of stoichiometric fit parameters. These were derived from the 16 inserts phantom scans and used to calculate CT numbers at 80 and 140 kVp for a set of tabulated reference human tissues. Model parameters for the parameterization of [Formula: see text] were estimated for this reference tissue dataset and compared to the results of the TSM. Residuals on Zeff for the reference tissue dataset for both TSM and RTM were compared to those obtained from the spectral method. The
Bourlès, Henri
2013-01-01
Linear systems have all the necessary elements (modeling, identification, analysis and control), from an educational point of view, to help us understand the discipline of automation and apply it efficiently. This book is progressive and organized in such a way that different levels of readership are possible. It is addressed both to beginners and those with a good understanding of automation wishing to enhance their knowledge on the subject. The theory is rigorously developed and illustrated by numerous examples which can be reproduced with the help of appropriate computation software. 60 exe
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Fabio Abel Gómez Becerra
2015-01-01
Full Text Available The use of linear slide system has been augmented in recent times due to features granted to supplement electromechanical systems; new technologies have allowed the manufacture of these systems with low coefficients of friction and offer a variety of types of sliding. In this paper, we present a comparison between the performance indexes of two techniques of control applying optimal control LQR (Linear Quadratic Regulator acronym for STIs in English and the technique of differential flatness controller. The use of linear slide bolt of potency takes into account the dynamics of the DC motor; the Euler-Lagrange formalism was used to establish the mathematical model of the slide. Cosimulation via the MATLAB/Simulink-ADAMS virtual prototype package, including realistic measurement disturbances, is used to compare the performance indexes between the LQR controller versus differential flatness controller for the position tracking of linear guide system.
Energy Technology Data Exchange (ETDEWEB)
Saucier, Antoine [Ecole Polytechnique de Montreal, C.P. 6079, Station centre-ville, Montreal (Que.), H3C-3A7 (Canada)]. E-mail: Antoine.Saucier@polymtl.ca; Soumis, Francois [Ecole Polytechnique de Montreal, C.P. 6079, Station centre-ville, Montreal (Que.), H3C-3A7 (Canada)]. E-mail: Francois.Soumis@gerad.ca
2006-06-15
The characterization of irregular objects with fractal methods often leads to the estimation of the slope of a function which is plotted versus a scale parameter. The slope is usually obtained with a linear regression. The problem is that the fit is usually not acceptable from the statistical standpoint. We propose a new approach in which we use two straight lines to bound the data from above and from below. We call these lines the upper and lower linear bounds. We propose to define these bounds as the solution of an optimization problem. We discuss the solution of this problem and we give an algorithm to obtain its solution. We use the difference between the upper and lower linear bounds to define a measure of the degree of linearity in the scaling range. We illustrate our method by analyzing the fluctuations of the variogram in a microresistivity well log from an oil reservoir in the North Sea.
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Jose Isagani Janairo
2011-08-01
Full Text Available The activity of a selected class of DPP4 inhibitors was preliminarily assessed using chemical descriptors derived AM1 optimized geometries. Using multiple linear regression model, it was found that ?E0, LUMO energy, area, molecular weight and ?H0 are the significant descriptors that can adequately assess the binding affinity of the compounds. The derived multiple linear regression (MLR model was validated using rigorous statistical analysis. The preliminary model suggests that bulky and electrophilic inhibitors are desired.
Linearity in Process Languages
DEFF Research Database (Denmark)
Nygaard, Mikkel; Winskel, Glynn
2002-01-01
The meaning and mathematical consequences of linearity (managing without a presumed ability to copy) are studied for a path-based model of processes which is also a model of affine-linear logic. This connection yields an affine-linear language for processes, automatically respecting open......-map bisimulation, in which a range of process operations can be expressed. An operational semantics is provided for the tensor fragment of the language. Different ways to make assemblies of processes lead to different choices of exponential, some of which respect bisimulation....
Clement, Dominic; Gruber, Nicolas
2017-04-01
Major progress has been made by the international community (e.g., GO-SHIP, IOCCP, IMBER/SOLAS carbon working groups) in recent years by collecting and providing homogenized datasets for carbon and other biogeochemical variables in the surface ocean (SOCAT) and interior ocean (GLODAPv2). Together with previous efforts, this has enabled the community to develop methods to assess changes in the ocean carbon cycle through time. Of particular interest is the determination of the decadal change in the anthropogenic CO2 inventory solely based on in-situ measurements from at least two time periods in the interior ocean. However, all such methods face the difficulty of a scarce dataset in both space and time, making the use of appropriate interpolation techniques in time and space a crucial element of any method. Here we present a new method based on the parameter C*, whose variations reflect the total change in dissolved inorganic carbon (DIC) driven by the exchange of CO2 across the air-sea interface. We apply the extended Multiple Linear Regression method (Friis et al., 2005) on C* in order (1) to calculate the change in anthropogenic CO2 from the original DIC/C* measurements, and (2) to interpolate the result onto a spatial grid using other biogeochemical variables (T,S,AOU, etc.). These calculations are made on isopycnal slabs across whole ocean basins. In combination with the transient steady state assumption (Tanhua et al., 2007) providing a temporal correction factor, we address the spatial and temporal interpolation challenges. Using synthetic data from a hindcast simulation with a global ocean biogeochemistry model (NCAR-CCSM with BEC), we tested the method for robustness and accuracy in determining ΔCant. We will present data-based results for all ocean basins, with the most recent estimate of an global uptake of 32±6 Pg C between 1994 and 2007, indicating an uptake rate 2.5±0.5 Pg C yr-1 for this time period. These results are compared with regional and
Ren, Wanting
2007-12-01
Soft materials have attracted much scientific and technical interest in recent years. In this thesis, attention has been placed on the underpinning relations between molecular structure and properties of one type of soft matter---main chain liquid crystalline elastomers (MCLCEs), which may have application as shape memory or as auxetic materials. In this work, a number of siloxane-based MCLCEs and their linear polymer analogues (MCLCEs) with chemical variations were synthesized and examined. Among these chemical variations, rigid p-phenylene transverse rod and flat-shaped anthraquinone (AQ) mesogenic monomers were specifically incorporated. Thermal and X-ray analysis found a smectic C phase in most of our MCLCEs, which was induced by the strong self-segregation of siloxane spacers, hydrocarbon spacers and mesogenic rods. The smectic C mesophase of the parent LCE was not grossly affected by terphenyl transverse rods. Mechanical studies of MCLCEs indicated the typical three-region stress-strain curve and a polydomain-to-monodomain transition. Strain recovery experiments of MCLCEs showed a significant dependence of strain retentions on the initial strains but not on the chemical variations, such as the crosslinker content and the lateral substituents on mesogenic rods. The MCLCE with p-phenylene transverse rod showed a highly ordered smectic A mesophase at room temperature with high stiffness. Mechanical properties of MCLCEs with AQ monomers exhibit a strong dependence on the specific combination of hydrocarbon spacer and siloxane spacer, which also strongly affect the formation of pi-pi stacking between AQ units. Poisson's ratio measurement over a wide strain range found distinct trends of Poisson's ratio as a function of the crosslinker content as well as terphenyl transverse rod loadings in its parent MCLCEs.
Flores-Martinez, Everardo; Malin, Martha J.; DeWerd, Larry A.
2016-11-01
The quantity of relevance for external beam radiotherapy is absorbed dose to water (ADW). An interferometer was built, characterized, and tested to measure ADW within the dose range of interest for external beam radiotherapy using the temperature dependence of the refractive index of water. The interferometer was used to measure radiation-induced phase shifts of a laser beam passing through a (10 × 10 × 10) cm3 water-filled glass phantom, irradiated with a 6 MV photon beam from a medical linear accelerator. The field size was (7 × 7) cm2 and the dose was measured at a depth of 5 cm in the water phantom. The intensity of the interference pattern was measured with a photodiode and was used to calculate the time-dependent phase shift curve. The system was thermally insulated to achieve temperature drifts of less than 1.5 mK/min. Data were acquired 60 s before and after the irradiation. The radiation-induced phase shifts were calculated by taking the difference in the pre- and post-irradiation drifts extrapolated to the midpoint of the irradiation. For 200, 300, and 400 monitor units, the measured doses were 1.6 ± 0.3, 2.6 ± 0.3, and 3.1 ± 0.3 Gy, respectively. Measurements agreed within the uncertainty with dose calculations performed with a treatment planning system. The estimated type-A, k = 1 uncertainty in the measured doses was 0.3 Gy which is an order of magnitude lower than previously published interferometer-based ADW measurements.
Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan
2017-02-20
The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.
Linear birefringence and dichroism measurement in oil-based Fe{sub 3}O{sub 4} magnetic nanoparticles
Energy Technology Data Exchange (ETDEWEB)
Lin, Jing-Fung, E-mail: jacklin@cc.feu.edu.tw [Graduate School of Computer Application Engineering, Far East University, Tainan 74448, Taiwan (China); Wang, Chia-Hung [Department of Automation and Control Engineering, Far East University, Tainan 74448, Taiwan (China); Lee, Meng-Zhe [Graduate School of Computer Application Engineering, Far East University, Tainan 74448, Taiwan (China)
2013-04-15
To prepare dispersed Fe{sub 3}O{sub 4} magnetic nanoparticles (MNPs), we adopt a co-precipitation method and consider surfactant amount, stirring speed, dispersion mode, and molar ratio of Fe{sup 3+}/Fe{sup 2+}. Via transmission electronic microscopy and X-ray diffractometry, we characterize the dispersibility and size of the products and determine the appropriate values of experimental parameters. The stirring speed is 1000 rpm in titration. There is simultaneous ultrasonic vibration and mechanical stirring in the titration and surface coating processes. The surfactant amount of oleic acid is 1.2 ml for molar ratios of Fe{sup 3+}/Fe{sup 2+} as 1.7:1, 1.8:1, and 1.9:1. The average diameters of these Fe{sub 3}O{sub 4} MNPs are 11 nm, and the ratios of saturation magnetization for these MNPs to that of bulk magnetite range from 45% to 65%, with remanent magnetization close to zero and low coercivity. Above all, the linear birefringence and dichroism measurements of the kerosene-based ferrofluid (FF) samples are investigated by a Stokes polarimeter. The influences of particle size distribution and magnetization in the birefringence and dichroism measurements of FFs are discussed. - Highlights: ► Dispersed Fe{sub 3}O{sub 4} magnetic nanoparticles (MNPs) are produced by a co-precipitation method. ► Simultaneous ultrasonic vibration and mechanical stirring are used in titration and coating. ► Diameters of Fe{sub 3}O{sub 4} MNPs are determined as 11 nm with maximum magnetization as 54.27 emu/g. ► Birefringence and dichroism of ferrofluids are obtained by a Stokes polarimeter successfully.
Zadurska, M; Sandham, J A; Wohlgemuth, B
1990-06-01
The use of a computer is described to make linear and angular measurements of the base of the skull. A group of 19 adult skulls from mediaeval Poland were chosen for this study. The cephalometric analysis defined 11 linear and 9 angular morphological variables. An assessment of method error due to point location by the cursor was made by duplicate determination, and an assessment of symmetry was carried out by comparing angular values derived from basion (ba) for right and left sides of the maxillary dental arch, zygomatic arch and cranial base. The results demonstrate that skull measurements could be recorded with a small method error of 0.2 mm for linear, and 0.2 degrees for angular recordings. Mean values for the 21 variables in the sample were recorded and statistically tested for point placement accuracy using measures of skewness and kurtosis to detect gross distribution errors.
Ligier, Nicolas; Carter, John; Poulet, François; Langevin, Yves; Dumas, Christophe; Gourgeot, Florian
2016-04-01
Jupiter's moon Europa harbors a very young surface dated, based on cratering rates, to 10-50 M.y (Zahnle et al. 1998, Pappalardo et al. 1999). This young age implies rapid surface recycling and reprocessing, partially engendered by a global salty subsurface liquid ocean that could result in tectonic activity (Schmidt et al. 2011, Kattenhorn et al. 2014) and active plumes (Roth et al. 2014). The surface of Europa should contain important clues about the composition of this sub-surface briny ocean and about the potential presence of material of exobiological interest in it, thus reinforcing Europa as a major target of interest for upcoming space missions such as the ESA L-class mission JUICE. To perform the investigation of the composition of the surface of Europa, a global mapping campaign of the satellite was performed between October 2011 and January 2012 with the integral field spectrograph SINFONI on the Very Large Telescope (VLT) in Chile. The high spectral binning of this instrument (0.5 nm) is suitable to detect any narrow mineral signature in the wavelength range 1.45-2.45 μm. The spatially resolved spectra we obtained over five epochs nearly cover the entire surface of Europa with a pixel scale of 12.5 by 25 m.a.s (~35 by 70 km on Europa's surface), thus permitting a global scale study. Until recently, a large majority of studies only proposed sulfate salts along with sulfuric acid hydrate and water-ice to be present on Europa's surface. However, recent works based on Europa's surface coloration in the visible wavelength range and NIR spectral analysis support the hypothesis of the predominance of chlorine salts instead of sulfate salts (Hand & Carlson 2015, Fischer et al. 2015). Our linear spectral modeling supports this new hypothesis insofar as the use of Mg-bearing chlorines improved the fits whatever the region. As expected, the distribution of sulfuric acid hydrate is correlated to the Iogenic sulfur ion implantation flux distribution (Hendrix et al
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López Rodrigo
2008-05-01
Full Text Available Abstract Background The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. Results We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. Conclusion The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable.
Yan, Siqi; Gao, Shengqian; Zhou, Feng; Ding, Yunhong; Dong, Jianji; Cai, Xinlun; Zhang, Xinliang
2017-09-01
A novel concept to generate a linear chirped microwave signal is proposed and experimentally demonstrated. The frequency to time mapping method is employed, where the photonic crystal waveguide Mach-Zehnder interferometer structure acts as the spectral shaper thanks to the slow light effect. By optimizing the structural parameters of the photonic crystal waveguide, a linear chirped microwave signal with the time-bandwidth product of about 30 is experimentally obtained. The impact of the slow light photonic crystal waveguide on the generated linear chirped microwave signal is also investigated. The utilization of the slow light effect brings in significant advantages, including the ultra-small footprint of 0.096 mm2 and simple structure to our scheme, which may be of great importance towards its potential applications.
DEFF Research Database (Denmark)
Yan, Siqi; Gao, Shengqian; Zhou, Feng
2017-01-01
A novel concept to generate a linear chirped microwave signal is proposed and experimentally demonstrated. The frequency to time mapping method is employed, where the photonic crystal waveguide Mach-Zehnder interferometer structure acts as the spectral shaper thanks to the slow light effect....... By optimizing the structural parameters of the photonic crystal waveguide, a linear chirped microwave signal with the time-bandwidth product of about 30 is experimentally obtained. The impact of the slow light photonic crystal waveguide on the generated linear chirped microwave signal is also investigated....... The utilization of the slow light effect brings in significant advantages, including the ultra-small footprint of 0.096 mm(2) and simple structure to our scheme, which may be of great importance towards its potential applications. (C) 2017 Optical Society of America...
Directory of Open Access Journals (Sweden)
Hyung-Seok Lee
2014-08-01
Full Text Available A linearized wavelength-swept thermo-optic laser chip was applied to demonstrate a fiber Bragg grating (FBG sensor interrogation system. A broad tuning range of 11.8 nm was periodically obtained from the laser chip for a sweep rate of 16 Hz. To measure the linear time response of the reflection signal from the FBG sensor, a programmed driving signal was directly applied to the wavelength-swept laser chip. The linear wavelength response of the applied strain was clearly extracted with an R-squared value of 0.99994. To test the feasibility of the system for dynamic measurements, the dynamic strain was successfully interrogated with a repetition rate of 0.2 Hz by using this FBG sensor interrogation system.
Neural network-based robust actuator fault diagnosis for a non-linear multi-tank system.
Mrugalski, Marcin; Luzar, Marcel; Pazera, Marcin; Witczak, Marcin; Aubrun, Christophe
2016-03-01
The paper is devoted to the problem of the robust actuator fault diagnosis of the dynamic non-linear systems. In the proposed method, it is assumed that the diagnosed system can be modelled by the recurrent neural network, which can be transformed into the linear parameter varying form. Such a system description allows developing the designing scheme of the robust unknown input observer within H∞ framework for a class of non-linear systems. The proposed approach is designed in such a way that a prescribed disturbance attenuation level is achieved with respect to the actuator fault estimation error, while guaranteeing the convergence of the observer. The application of the robust unknown input observer enables actuator fault estimation, which allows applying the developed approach to the fault tolerant control tasks. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Edlund, Kristian
2013-01-01
In this paper, we develop an efficient interior-point method (IPM) for the linear programs arising in economic model predictive control of linear systems. The novelty of our algorithm is that it combines a homogeneous and self-dual model, and a specialized Riccati iteration procedure. We test...... the algorithm in a conceptual study of power systems management. Simulations show that in comparison to state of the art software implementation of IPMs, our method is significantly faster and scales in a favourable way....
Directory of Open Access Journals (Sweden)
Penghan Li
2017-08-01
Full Text Available The increasing penetration of wind power in the grid has driven the integration of wind farms with power systems that are series-compensated to enhance power transfer capability and dynamic stability. This may lead to sub-synchronous control interaction (SSCI problems in series-compensated doubly-fed induction generator (DFIG-based wind farms. To mitigate SSCI, nonlinear controllers based on exact feedback linearization (EFL are proposed in this paper. Before deriving the control laws, the exact feedback linearizability of the studied system is scrutinized. Frequency scanning analysis is employed to test the designed EFL controllers. Moreover, the performance of the EFL controllers is compared to that of classical proportional-integral (PI controllers. A series-compensated 100 MW DFIG-based wind park is utilized to assess the performance of the designed controllers through the alleviation of sub-synchronous resonance. Analyses of the studied system reveal that the resistance is negative under sub-synchronous frequency conditions, whereas the reactance becomes negative at approximately 44 Hz. The designed EFL controllers effectively alleviate SSCI and result in positive reactance and resistance values within the whole sub-synchronous frequency range. The results from the frequency scanning method are also validated through the time domain simulation and the eigenvalue analysis.
Arisanti, R.; Notodiputro, K. A.; Sadik, K.; Lim, A.
2017-03-01
There are two approaches in estimating variance components, i.e. linearity and integral approaches. However the estimates of variance components produced by both methods are known to be biased. Firth (1993) has introduced parameter estimation for correcting the bias of the maximum likelihood estimates. This method is within the class of linear models, especially the Restricted Maximum Likelihood (REML) method, and the resulting estimator is known as the Firth estimator. In this paper we discuss the bias correction method applied to a logistic linear mixed model in analyzing the existence of Synedra phytoplankton along Na Thap river in Thailand. The Firth adjusted Maximum Likelihood Estimation (MLE) is similar to REML but it shows the characteristic of generalized linear mixed model. We evaluated the Firth adjustment method by means of simulations and the result showed that the unadjusted MLE produced 95% confidence intervals which were narrower when compare to the Firth method. However, the probability coverage of the interval for unadjusted MLE was lower than 95%, whereas for the Firth method the probability coverage is approximately 95%. These results were also consistent with the variance estimation of the Synedra phytoplankton existence. It was shown that the variance estimates of Firth adjusted MLE was lower than the unadjusted MLE.
F.D. Barb
2004-01-01
textabstractIn this paper we address the problem of reducing the order of a linear system affected by uncertainties from the robust dissipative perspective introduced in Barb. Firstly, we show that all major balanced truncation techniques developed and reported in the literature of the last two
S.-C. Fang; J. Han; Z. Huang (Zhen); S.I. Birbil (Ilker)
2002-01-01
textabstractBy using a smooth entropy function to approximate the non-smooth max-type function, a vertical linear complementarity problem (VLCP) can be treated as a family of parameterized smooth equations. A Newton-type method with a testing procedure is proposed to solve such a system. We show
S.I. Birbil (Ilker); S-C. Fang (Shu-Cherng); J. Han
2002-01-01
textabstractBy using a smooth entropy function to approximate the non-smooth max-type function, a vertical linear complementarity problem (VLCP) can be treated as a family of parameterized smooth equations. A Newton-type method with a testing procedure is proposed to solve such a system. We show
Namburu, R. R.; Tamma, K. K.
1991-01-01
The applicability and evaluation of a generalized gamma(T) family of flux-based representations are examined for two different thermal analysis formulations for structures and materials which exhibit no phase change effects. The so-called H-theta and theta forms are demonstrated for numerous test models and linear and higher-order elements. The results show that the theta form with flux-based representations is generally superior to traditional approaches.
Linearly Adjustable International Portfolios
Fonseca, R. J.; Kuhn, D.; Rustem, B.
2010-09-01
We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.
On the linear programming bound for linear Lee codes.
Astola, Helena; Tabus, Ioan
2016-01-01
Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.
Directory of Open Access Journals (Sweden)
Z. Mosayebi
2014-07-01
Full Text Available In this paper a numerical technique is presented for the solution of fuzzy linear Volterra-Fredholm-Hammerstein integral equations. This method is a combination of collocation method and radial basis functions(RBFs.We first solve the actual set are equivalent to the fuzzy set, then answer 1-cut into the equation. Also high convergence rates and good accuracy are obtain with the propose method using relativeiy low numbers of data points.
Vásquez Correa, Juan Camilo
2016-01-01
In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called "paralinguistic" aspects of the speech, including the emotions, and the personality of the speaker. This research work aims in the development of a methodology for the automatic emotion recognition from speech signals in non-controlled noise conditions. For that purpose, different sets of acoustic, non-linear, and wave...
Marrero-Ponce, Yovani; Martínez-Albelo, Eugenio R; Casañola-Martín, Gerardo M; Castillo-Garit, Juan A; Echevería-Díaz, Yunaimy; Zaldivar, Vicente Romero; Tygat, Jan; Borges, José E Rodriguez; García-Domenech, Ramón; Torrens, Francisco; Pérez-Giménez, Facundo
2010-11-01
Novel bond-level molecular descriptors are proposed, based on linear maps similar to the ones defined in algebra theory. The kth edge-adjacency matrix (E(k)) denotes the matrix of bond linear indices (non-stochastic) with regard to canonical basis set. The kth stochastic edge-adjacency matrix, ES(k), is here proposed as a new molecular representation easily calculated from E(k). Then, the kth stochastic bond linear indices are calculated using ES(k) as operators of linear transformations. In both cases, the bond-type formalism is developed. The kth non-stochastic and stochastic total linear indices are calculated by adding the kth non-stochastic and stochastic bond linear indices, respectively, of all bonds in molecule. First, the new bond-based molecular descriptors (MDs) are tested for suitability, for the QSPRs, by analyzing regressions of novel indices for selected physicochemical properties of octane isomers (first round). General performance of the new descriptors in this QSPR studies is evaluated with regard to the well-known sets of 2D/3D MDs. From the analysis, we can conclude that the non-stochastic and stochastic bond-based linear indices have an overall good modeling capability proving their usefulness in QSPR studies. Later, the novel bond-level MDs are also used for the description and prediction of the boiling point of 28 alkyl-alcohols (second round), and to the modeling of the specific rate constant (log k), partition coefficient (log P), as well as the antibacterial activity of 34 derivatives of 2-furylethylenes (third round). The comparison with other approaches (edge- and vertices-based connectivity indices, total and local spectral moments, and quantum chemical descriptors as well as E-state/biomolecular encounter parameters) exposes a good behavior of our method in this QSPR studies. Finally, the approach described in this study appears to be a very promising structural invariant, useful not only for QSPR studies but also for similarity
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.
Linear Classification Functions.
Huberty, Carl J.; Smith, Jerry D.
Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…
Linear Projective Program Syntax
Bergstra, J.A.; Bethke, I.
2004-01-01
Based on an extremely simple program notation more advanced program features can be developed in linear projective program syntax such as conditional statements, while loops, recursion, use of an evaluation stack, object classes, method calls etc. Taking care of a cumulative and bottom up
Guo, Yang; Riplinger, Christoph; Becker, Ute; Liakos, Dimitrios G; Minenkov, Yury; Cavallo, Luigi; Neese, Frank
2018-01-07
In this communication, an improved perturbative triples correction (T) algorithm for domain based local pair-natural orbital singles and doubles coupled cluster (DLPNO-CCSD) theory is reported. In our previous implementation, the semi-canonical approximation was used and linear scaling was achieved for both the DLPNO-CCSD and (T) parts of the calculation. In this work, we refer to this previous method as DLPNO-CCSD(T0) to emphasize the semi-canonical approximation. It is well-established that the DLPNO-CCSD method can predict very accurate absolute and relative energies with respect to the parent canonical CCSD method. However, the (T0) approximation may introduce significant errors in absolute energies as the triples correction grows up in magnitude. In the majority of cases, the relative energies from (T0) are as accurate as the canonical (T) results of themselves. Unfortunately, in rare cases and in particular for small gap systems, the (T0) approximation breaks down and relative energies show large deviations from the parent canonical CCSD(T) results. To address this problem, an iterative (T) algorithm based on the previous DLPNO-CCSD(T0) algorithm has been implemented [abbreviated here as DLPNO-CCSD(T)]. Using triples natural orbitals to represent the virtual spaces for triples amplitudes, storage bottlenecks are avoided. Various carefully designed approximations ease the computational burden such that overall, the increase in the DLPNO-(T) calculation time over DLPNO-(T0) only amounts to a factor of about two (depending on the basis set). Benchmark calculations for the GMTKN30 database show that compared to DLPNO-CCSD(T0), the errors in absolute energies are greatly reduced and relative energies are moderately improved. The particularly problematic case of cumulene chains of increasing lengths is also successfully addressed by DLPNO-CCSD(T).
Guo, Yang
2018-01-04
In this communication, an improved perturbative triples correction (T) algorithm for domain based local pair-natural orbital singles and doubles coupled cluster (DLPNO-CCSD) theory is reported. In our previous implementation, the semi-canonical approximation was used and linear scaling was achieved for both the DLPNO-CCSD and (T) parts of the calculation. In this work, we refer to this previous method as DLPNO-CCSD(T0) to emphasize the semi-canonical approximation. It is well-established that the DLPNO-CCSD method can predict very accurate absolute and relative energies with respect to the parent canonical CCSD method. However, the (T0) approximation may introduce significant errors in absolute energies as the triples correction grows up in magnitude. In the majority of cases, the relative energies from (T0) are as accurate as the canonical (T) results of themselves. Unfortunately, in rare cases and in particular for small gap systems, the (T0) approximation breaks down and relative energies show large deviations from the parent canonical CCSD(T) results. To address this problem, an iterative (T) algorithm based on the previous DLPNO-CCSD(T0) algorithm has been implemented [abbreviated here as DLPNO-CCSD(T)]. Using triples natural orbitals to represent the virtual spaces for triples amplitudes, storage bottlenecks are avoided. Various carefully designed approximations ease the computational burden such that overall, the increase in the DLPNO-(T) calculation time over DLPNO-(T0) only amounts to a factor of about two (depending on the basis set). Benchmark calculations for the GMTKN30 database show that compared to DLPNO-CCSD(T0), the errors in absolute energies are greatly reduced and relative energies are moderately improved. The particularly problematic case of cumulene chains of increasing lengths is also successfully addressed by DLPNO-CCSD(T).
Guo, Yang; Riplinger, Christoph; Becker, Ute; Liakos, Dimitrios G.; Minenkov, Yury; Cavallo, Luigi; Neese, Frank
2018-01-01
In this communication, an improved perturbative triples correction (T) algorithm for domain based local pair-natural orbital singles and doubles coupled cluster (DLPNO-CCSD) theory is reported. In our previous implementation, the semi-canonical approximation was used and linear scaling was achieved for both the DLPNO-CCSD and (T) parts of the calculation. In this work, we refer to this previous method as DLPNO-CCSD(T0) to emphasize the semi-canonical approximation. It is well-established that the DLPNO-CCSD method can predict very accurate absolute and relative energies with respect to the parent canonical CCSD method. However, the (T0) approximation may introduce significant errors in absolute energies as the triples correction grows up in magnitude. In the majority of cases, the relative energies from (T0) are as accurate as the canonical (T) results of themselves. Unfortunately, in rare cases and in particular for small gap systems, the (T0) approximation breaks down and relative energies show large deviations from the parent canonical CCSD(T) results. To address this problem, an iterative (T) algorithm based on the previous DLPNO-CCSD(T0) algorithm has been implemented [abbreviated here as DLPNO-CCSD(T)]. Using triples natural orbitals to represent the virtual spaces for triples amplitudes, storage bottlenecks are avoided. Various carefully designed approximations ease the computational burden such that overall, the increase in the DLPNO-(T) calculation time over DLPNO-(T0) only amounts to a factor of about two (depending on the basis set). Benchmark calculations for the GMTKN30 database show that compared to DLPNO-CCSD(T0), the errors in absolute energies are greatly reduced and relative energies are moderately improved. The particularly problematic case of cumulene chains of increasing lengths is also successfully addressed by DLPNO-CCSD(T).