In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the ε-insensitive loss function, admits of the residual within the boundary values of ε-tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.
Musafere, F.; Sadhu, A.; Liu, K.
2016-01-01
In the last few decades, structural health monitoring (SHM) has been an indispensable subject in the field of vibration engineering. With the aid of modern sensing technology, SHM has garnered significant attention towards diagnosis and risk management of large-scale civil structures and mechanical systems. In SHM, system identification is one of major building blocks through which unknown system parameters are extracted from vibration data of the structures. Such system information is then utilized to detect the damage instant, and its severity to rehabilitate and prolong the existing health of the structures. In recent years, blind source separation (BSS) algorithm has become one of the newly emerging advanced signal processing techniques for output-only system identification of civil structures. In this paper, a novel damage detection technique is proposed by integrating BSS with the time-varying auto-regressive modeling to identify the instant and severity of damage. The proposed method is validated using a suite of numerical studies and experimental models followed by a full-scale structure.
Permanasari, Adhistya Erna; Rambli, Dayang Rohaya Awang; Dominic, Dhanapal Durai
2009-01-01
Zoonosis refers to the transmission of infectious diseases from animal to human. The increasing number of zoonosis incidence makes the great losses to lives, including humans and animals, and also the impact in social economic. It motivates development of a system that can predict the future number of zoonosis occurrences in human. This paper analyses and presents the use of Seasonal Autoregressive Integrated Moving Average (SARIMA) method for developing a forecasting model that able to suppo...
Permanasari, Adhistya Erna; Dominic, Dhanapal Durai
2009-01-01
Zoonosis refers to the transmission of infectious diseases from animal to human. The increasing number of zoonosis incidence makes the great losses to lives, including humans and animals, and also the impact in social economic. It motivates development of a system that can predict the future number of zoonosis occurrences in human. This paper analyses and presents the use of Seasonal Autoregressive Integrated Moving Average (SARIMA) method for developing a forecasting model that able to support and provide prediction number of zoonosis human incidence. The dataset for model development was collected on a time series data of human tuberculosis occurrences in United States which comprises of fourteen years of monthly data obtained from a study published by Centers for Disease Control and Prevention (CDC). Several trial models of SARIMA were compared to obtain the most appropriate model. Then, diagnostic tests were used to determine model validity. The result showed that the SARIMA(9,0,14)(12,1,24)12 is the fitt...
The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models
Daniela Spiesová
2014-10-01
Full Text Available Currency market is recently the largest world market during the existence of which there have been many theories regarding the prediction of the development of exchange rates based on macroeconomic, microeconomic, statistic and other models. The aim of this paper is to identify the adequate model for the prediction of non-stationary time series of exchange rates and then use this model to predict the trend of the development of European currencies against Euro. The uniqueness of this paper is in the fact that there are many expert studies dealing with the prediction of the currency pairs rates of the American dollar with other currency but there is only a limited number of scientific studies concerned with the long-term prediction of European currencies with the help of the integrated ARMA models even though the development of exchange rates has a crucial impact on all levels of economy and its prediction is an important indicator for individual countries, banks, companies and businessmen as well as for investors. The results of this study confirm that to predict the conditional variance and then to estimate the future values of exchange rates, it is adequate to use the ARIMA (1,1,1 model without constant, or ARIMA [(1,7,1,(1,7] model, where in the long-term, the square root of the conditional variance inclines towards stable value.
Kepler AutoRegressive Planet Search
Caceres, Gabriel Antonio; Feigelson, Eric
2016-01-01
The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real
CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model
Dyrholm, Mads; Hansen, Lars Kai
2004-01-01
We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least square...... estimation. We demonstrate the method on synthetic data and finally separate speech and music in a real room recording....
CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model
Dyrholm, Mads; Hansen, Lars Kai
2004-01-01
We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least squares estimation. We demonstrate the method on synthetic data and finally separate speech and music in a real room recording.
Kepler AutoRegressive Planet Search: Motivation & Methodology
Caceres, Gabriel; Feigelson, Eric; Jogesh Babu, G.; Bahamonde, Natalia; Bertin, Karine; Christen, Alejandra; Curé, Michel; Meza, Cristian
2015-08-01
The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Auto-Regressive Moving-Average (ARMA) models, Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH), and related models are flexible, phenomenological methods used with great success to model stochastic temporal behaviors in many fields of study, particularly econometrics. Powerful statistical methods are implemented in the public statistical software environment R and its many packages. Modeling involves maximum likelihood fitting, model selection, and residual analysis. These techniques provide a useful framework to model stellar variability and are used in KARPS with the objective of reducing stellar noise to enhance opportunities to find as-yet-undiscovered planets. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; ARMA-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. We apply the procedures to simulated Kepler-like time series with known stellar and planetary signals to evaluate the effectiveness of the KARPS procedures. The ARMA-type modeling is effective at reducing stellar noise, but also reduces and transforms the transit signal into ingress/egress spikes. A periodogram based on the TCF is constructed to concentrate the signal
Hong-Juan Li
2013-04-01
Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents a SVR model hybridized with the empirical mode decomposition (EMD method and auto regression (AR for electric load forecasting. The electric load data of the New South Wales (Australia market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.
Drought Patterns Forecasting using an Auto-Regressive Logistic Model
del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.
2014-12-01
Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.
Steganalysis of LSB Image Steganography using Multiple Regression and Auto Regressive (AR Model
Souvik Bhattacharyya
2011-07-01
Full Text Available The staggering growth in communication technologyand usage of public domain channels (i.e. Internet has greatly facilitated transfer of data. However, such open communication channelshave greater vulnerability to security threats causing unauthorizedin- formation access. Traditionally, encryption is used to realizethen communication security. However, important information is notprotected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication.Important information is ﬁrstly hidden in a host data, such as digitalimage, text, video or audio, etc, and then transmitted secretly tothe receiver. Steganalysis is another important topic in informationhiding which is the art of detecting the presence of steganography. Inthis paper a novel technique for the steganalysis of Image has beenpresented. The proposed technique uses an auto-regressive model todetect the presence of the hidden messages, as well as to estimatethe relative length of the embedded messages.Various auto regressiveparameters are used to classify cover image as well as stego imagewith the help of a SVM classiﬁer. Multiple Regression analysis ofthe cover carrier along with the stego carrier has been carried outin order to ﬁnd out the existence of the negligible amount of thesecret message. Experimental results demonstrate the effectivenessand accuracy of the proposed technique.
Kepler AutoRegressive Planet Search: Initial Results
Caceres, Gabriel; Feigelson, Eric; Jogesh Babu, G.; Bahamonde, Natalia; Bertin, Karine; Christen, Alejandra; Curé, Michel; Meza, Cristian
2015-08-01
The statistical analysis procedures of the Kepler AutoRegressive Planet Search (KARPS) project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve, but visual inspection of the residual series shows that significant deviations from Gaussianity remain for many of them. Although the reduction in stellar signal is encouraging, it is important to note that the transit signal is also altered in the resulting residual time series. The periodogram derived from our Transit Comb Filter (TCF) is most effective for shorter period planets with quick ingress/egress times (relative to Kepler's 29-minute sample rate). We do not expect high sensitivity to periods of hundreds of days. Our findings to date on real-data tests of the KARPS methodology will be discussed including confirmation of some Kepler Team `candidate' planets, no confirmation of some `candidate' and `false positive' sytems, and suggestions of mischosen harmonics in the Kepler Team periodograms. We also present cases of new possible planetary signals.
Blind identification of threshold auto-regressive model for machine fault diagnosis
LI Zhinong; HE Yongyong; CHU Fulei; WU Zhaotong
2007-01-01
A blind identification method was developed for the threshold auto-regressive (TAR) model. The method had good identification accuracy and rapid convergence, especially for higher order systems. The proposed method was then combined with the hidden Markov model (HMM) to determine the auto-regressive (AR) coefficients for each interval used for feature extraction, with the HMM as a classifier. The fault diagnoses during the speed-up and speed- down processes for rotating machinery have been success- fully completed. The result of the experiment shows that the proposed method is practical and effective.
TIAN Lin-ya; HUA Xi-sheng
2007-01-01
To ensure the safety of buildings surrounding foundation pits, a study was made on a settlement monitoring and trend prediction method. A statistical testing method for analyzing the stability of a settlement monitoring datum has been discussed. According to a comprehensive survey, data of 16 stages at operating control point, were verified by a standard t test to determine the stability of the operating control point. A stationary auto-regression model, AR(p), used for the observation point settlement prediction has been investigated. Given the 16 stages of the settlement data at an observation point, the applicability of this model was analyzed. Settlement of last four stages was predicted using the stationary auto-regression model AR (1); the maximum difference between predicted and measured values was 0.6 mm,indicating good prediction results of the model. Hence, this model can be applied to settlement predictions for buildings surrounding foundation pits.
Zhao Haijun; Ma Yan; Huang Xiaohong; Su Yujie
2008-01-01
Predicting heartbeat message arrival time is crucial for the quality of failure detection service over internet. However, internet dynamic characteristics make it very difficult to understand message behavior and accurately predict heartbeat arrival time. To solve this problem, a novel black-box model is proposed to predict the next heartbeat arrival time. Heartbeat arrival time is modeled as auto-regressive process, heartbeat sending time is modeled as exogenous variable, the model's coefficients are estimated based on the sliding window of observations and this result is used to predict the next heartbeat arrival time. Simulation shows that this adaptive auto-regressive exogenous (ARX) model can accurately capture heartbeat arrival dynamics and minimize prediction error in different network environments.
Probing turbulence intermittency via Auto-Regressive Moving-Average models
Faranda, Davide; Dubrulle, Berengere; Daviaud, Francois
2014-01-01
We suggest a new approach to probing intermittency corrections to the Kolmogorov law in turbulent flows based on the Auto-Regressive Moving-Average modeling of turbulent time series. We introduce a new index $\\Upsilon$ that measures the distance from a Kolmogorov-Obukhov model in the Auto-Regressive Moving-Average models space. Applying our analysis to Particle Image Velocimetry and Laser Doppler Velocimetry measurements in a von K\\'arm\\'an swirling flow, we show that $\\Upsilon$ is proportional to the traditional intermittency correction computed from the structure function. Therefore it provides the same information, using much shorter time series. We conclude that $\\Upsilon$ is a suitable index to reconstruct the spatial intermittency of the dissipation in both numerical and experimental turbulent fields.
A DEOXYRIBONUCLEIC ACID COMPRESSION ALGORITHM USING AUTO-REGRESSION AND SWARM INTELLIGENCE
Walid Aly
2013-01-01
Full Text Available DNA compression challenge has become a major task for many researchers as a result of exponential increase of produced DNA sequences in gene databases; in this research we attempt to solve the DNA compression challenge by developing a lossless compression algorithm. The proposed algorithm works in horizontal mode using a substitutional-statistical technique which is based on Auto Regression modeling (AR, the model parameters are determined using Particle Swarm Optimization (PSO. This algorithm is called Swarm Auto-Regression DNA Compression (SARDNAComp. SARDNAComp aims to reach higher compression ratio which make its application beneficial for both practical and functional aspects due to reduction of storage, retrieval, transmission costs and inferring structure and function of sequences from compression, SARDNAComp is tested on eleven benchmark DNA sequences and compared to current algorithms of DNA compression, the results showed that (SARDNAComp outperform these algorithms.
Time-varying parameter auto-regressive models for autocovariance nonstationary time series
无
2009-01-01
In this paper, autocovariance nonstationary time series is clearly defined on a family of time series. We propose three types of TVPAR (time-varying parameter auto-regressive) models: the full order TVPAR model, the time-unvarying order TVPAR model and the time-varying order TV-PAR model for autocovariance nonstationary time series. Related minimum AIC (Akaike information criterion) estimations are carried out.
Time-varying parameter auto-regressive models for autocovariance nonstationary time series
FEI WanChun; BAI Lun
2009-01-01
In this paper,autocovariance nonstationary time series is clearly defined on a family of time series.We propose three types of TVPAR (time-varying parameter auto-regressive) models:the full order TVPAR model,the time-unvarying order TVPAR model and the time-varying order TVPAR model for autocovariance nonstationary time series.Related minimum AIC (Akaike information criterion) estimations are carried out.
For the past two decades, the nuclear industry has attempted to move towards condition-based maintenance philosophies using new technologies developed to ascertain the condition of plant equipment during operation. From the early 1980's the application of artificial intelligence techniques to nuclear power plants were investigated for instrument condition monitoring. The Multivariate State Estimation System (MSET) was developed in the late 1980s. And the Plant Evaluation and Analysis by Neural Operators (PEANO) was developed; it uses auto associative neural networks (AANN) and applies them to the monitoring of nuclear power plant sensors. In this paper, a method that utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and Auto- Associative support vector regression (AASVR) for databased statistical learning is proposed for the on-line monitoring and signal validation with the use of real plant data
An Integration of Math with Auto Technician Courses
Valenzuela, Hector
2012-01-01
This article describes the development of the contextualized math, the course design, student teaching and daily interaction with the students, and the implementation aspects of the research project designed to develop contextualized mathematics and integrate it into the Auto Technician courses. The applied math curriculum was integrated into…
Statistical early-warning indicators based on Auto-Regressive Moving-Average processes
Faranda, Davide; Dubrulle, Bérengère
2014-01-01
We address the problem of defining early warning indicators of critical transition. To this purpose, we fit the relevant time series through a class of linear models, known as Auto-Regressive Moving-Average (ARMA(p,q)) models. We define two indicators representing the total order and the total persistence of the process, linked, respectively, to the shape and to the characteristic decay time of the autocorrelation function of the process. We successfully test the method to detect transitions in a Langevin model and a 2D Ising model with nearest-neighbour interaction. We then apply the method to complex systems, namely for dynamo thresholds and financial crisis detection.
Linking Simple Economic Theory Models and the Cointegrated Vector AutoRegressive Model
Møller, Niels Framroze
This paper attempts to clarify the connection between simple economic theory models and the approach of the Cointegrated Vector-Auto-Regressive model (CVAR). By considering (stylized) examples of simple static equilibrium models, it is illustrated in detail, how the theoretical model and its stru....... Further fundamental extensions and advances to more sophisticated theory models, such as those related to dynamics and expectations (in the structural relations) are left for future papers......This paper attempts to clarify the connection between simple economic theory models and the approach of the Cointegrated Vector-Auto-Regressive model (CVAR). By considering (stylized) examples of simple static equilibrium models, it is illustrated in detail, how the theoretical model and its...... demonstrated how other controversial hypotheses such as Rational Expectations can be formulated directly as restrictions on the CVAR-parameters. A simple example of a "Neoclassical synthetic" AS-AD model is also formulated. Finally, the partial- general equilibrium distinction is related to the CVAR as well...
Gammelgaard Nielsen, Anders; Aagaard, Tine; Diaz, pauline;
2011-01-01
AUTO is the first assignment that the students of Architecture are introduced to at the Aarhus school of Architecture. The aim is to give students an understanding of design through a generic working method. This by disassembling a car engine and staging its components through a series of castings...
Modelling and analysis of turbulent datasets using Auto Regressive Moving Average processes
We introduce a novel way to extract information from turbulent datasets by applying an Auto Regressive Moving Average (ARMA) statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations and links the behavior of the recorded time series to a discrete version of a stochastic differential equation which is able to describe the correlation structure in the dataset. We introduce a new index Υ that measures the difference between the resulting analysis and the Obukhov model of turbulence, the simplest stochastic model reproducing both Richardson law and the Kolmogorov spectrum. We test the method on datasets measured in a von Kármán swirling flow experiment. We found that the ARMA analysis is well correlated with spatial structures of the flow, and can discriminate between two different flows with comparable mean velocities, obtained by changing the forcing. Moreover, we show that the Υ is highest in regions where shear layer vortices are present, thereby establishing a link between deviations from the Kolmogorov model and coherent structures. These deviations are consistent with the ones observed by computing the Hurst exponents for the same time series. We show that some salient features of the analysis are preserved when considering global instead of local observables. Finally, we analyze flow configurations with multistability features where the ARMA technique is efficient in discriminating different stability branches of the system
The observation of the equipment and piping system installed in an operating nuclear power plant in earthquakes is very umportant for evaluating and confirming the adequacy and the safety margin expected in the design stage. By analyzing observed earthquake records, it can be expected to get the valuable data concerning the behavior of those in earthquakes, and extract the information about the aseismatic design parameters for those systems. From these viewpoints, an earthquake observation system was installed in a reactor building in an operating plant. Up to now, the records of three earthquakes were obtained with this system. In this paper, an example of the analysis of earthquake records is shown, and the main purpose of the analysis was the evaluation of the vibration mode, natural frequency and damping factor of this piping system. Prior to the earthquake record analysis, the eigenvalue analysis for this piping system was performed. Auto-regressive analysis was applied to the observed acceleration time history which was obtained with a piping system installed in an operating BWR. The results of earthquake record analysis agreed well with the results of eigenvalue analysis. (Kako, I.)
Day-ahead prediction using time series partitioning with Auto-Regressive model
Dennis Cheruiyot Kiplangat
2016-08-01
Full Text Available Wind speed forecasting has received a lot of attention in the recent past from researchers due to its enormous benefits in the generation of wind power and distribution. The biggest challenge still remains to be accurate prediction of wind speeds for efficient operation of a wind farm. Wind speed forecasts can be greatly improved by understanding its underlying dynamics. In this paper, we propose a method of time series partitioning where the original 10 minutes wind speed data is converted into a twodimensional array of order (N x 144 where N denotes the number of days with 144 the daily 10-min observations. Upon successful time series partitioning, a point forecast is computed for each of the 144 datasets extracted from the 10 minutes wind speed observations using an Auto-Regressive (AR process which is then combined together to give the (N+1st day forecast. The results of the computations show significant improvement in the prediction accuracy when AR model is coupled with time series partitioning.
SURFACE INTEGRITY EVALUATION OF TURNING WITH AUTO-ROTATING TOOL
Jozef Struharnansky
2016-09-01
Full Text Available The technical practice requirements comes to have increased demands on higher productivity, speed and quality of the machining process of various materials. Hard to machine materials, whose machining led to the development of turning with rotating cutting edge are not an exception. The machining process of auto-rotating tool is more complicated than the conventional process of turning, especially for the process of reshaping cutting layers into chips. There is a significant load in the system, that may affect the life of the cutting edge of the tool as well as the whole system and also in the final extent of the qualitative parameters of the workpiece (product / product. The article specifies the knowledge and findings of measurement in machining material 100Cr6 with an auto-rotating tool. The measurements were conducted to evaluate the integrity of the surface (roughness of the workpiece to the impacts of cutting conditions, in particular the feed and the cutting edge inclination. It also analyzes the presence (size, character, action of residual stresses concentrated in the surface layers of the workpiece by changing the cutting conditions.
Li, Chunjian; Andersen, Søren Vang
2007-01-01
We propose two blind system identification methods that exploit the underlying dynamics of non-Gaussian signals. The two signal models to be identified are: an Auto-Regressive (AR) model driven by a discrete-state Hidden Markov process, and the same model whose output is perturbed by white Gaussian...... iterative schemes. The proposed methods also enjoy good data efficiency since only second order statistics is involved in the computation. When measurement noise is present, a novel Switching Kalman Smoother is incorporated into the EM algorithm, obtaining optimum nonlinear MMSE estimates of the system...
The problem of performing process capability analysis when auto correlations are present is discussed. It is shown that when the systematic nonrandom phenomenon induced by autocorrelation is ignored the variance estimate obtained from the original data is no longer an appropriate estimate for use in the process capability analyses. A remedial measure based on an autoregressive integrated moving average model is proposed. It is also shown that the process variance estimated from the residual analysis yields appropriate results for the process capability indices
In the present paper the step response methods for system time constant is described, revealing the connections between auto-regression coefficients and transient functions for a given system. The general calculational results obtained through this method this method (ARSTEP algorithm) for thermocouple, ionization chambers, and self powered detectors used in Nuclear Power Plant are given. The typical transfer function for there detectors and for the physical system described by means of the third order differential equation as well as transfer function for dynamical processes of reactor core is found. On these bases, and with the aim to made it useful also for the neutronic al sensors, a new algorithm for improving the ARSTEP code system is proposed
Baraldi, Piero; Di Maio, Francesco; Turati, Pietro; Zio, Enrico
2015-08-01
In this work, we propose a modification of the traditional Auto Associative Kernel Regression (AAKR) method which enhances the signal reconstruction robustness, i.e., the capability of reconstructing abnormal signals to the values expected in normal conditions. The modification is based on the definition of a new procedure for the computation of the similarity between the present measurements and the historical patterns used to perform the signal reconstructions. The underlying conjecture for this is that malfunctions causing variations of a small number of signals are more frequent than those causing variations of a large number of signals. The proposed method has been applied to real normal condition data collected in an industrial plant for energy production. Its performance has been verified considering synthetic and real malfunctioning. The obtained results show an improvement in the early detection of abnormal conditions and the correct identification of the signals responsible of triggering the detection.
Rebora, N.; Silvestro, F.; Rudari, R.; Herold, C.; Ferraris, L.
2016-06-01
Downscaling methods are used to derive stream flow at a high temporal resolution from a data series that has a coarser time resolution. These algorithms are useful for many applications, such as water management and statistical analysis, because in many cases stream flow time series are available with coarse temporal steps (monthly), especially when considering historical data; however, in many cases, data that have a finer temporal resolution are needed (daily). In this study, we considered a simple but efficient stochastic auto-regressive model that is able to downscale the available stream flow data from monthly to daily time resolution and applied it to a large dataset that covered the entire North and Central American continent. Basins with different drainage areas and different hydro-climatic characteristics were considered, and the results show the general good ability of the analysed model to downscale monthly stream flows to daily stream flows, especially regarding the reproduction of the annual maxima. If the performance in terms of the reproduction of hydrographs and duration curves is considered, better results are obtained for those cases in which the hydrologic regime is such that the annual maxima stream flow show low or medium variability, which means that they have a low or medium coefficient of variation; however, when the variability increases, the performance of the model decreases.
Hory, C.; Bouillaut, L.; Aknin, P.
2012-05-01
Rail corrugation is an oscillatory mechanical wear of rail surface raising from the long-term interaction between rail and wheel. Signal processing approaches to corrugation monitoring, as recommended by the European standards for instance, are designed either in the mileage domain or in the wavelength domain. However a joint mileage and wavelength domain analysis of the monitoring data can provide crucial information about the simultaneous amplitude and wavelength modulations of the corrugation modes. It is proposed in this paper to perform such a mileage-wavelength domain analysis of rail corrugation using the class of Auto-Regressive-MAtched Filterbank (AR-MAFI) methods. We show that these methods assume a statistical model that fits the corrugation data. We discuss also the optimal parameter settings for the analysis of corrugation data. Experimental studies performed on data collected from the French RATP metro network show that the AR-MAFI methods outperform (in terms of readability and accuracy) the standard distance domain or wavelength domain methods in localizing and characterizing corrugation.
Abdel K.M. Baareh
2006-01-01
Full Text Available Forecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN became quite successful tool to handle time series modeling problem. This paper provides a solution to the forecasting problem of the river flow for two well known Rivers in the USA. They are the Black Water River and the Gila River. The selected ANN models were used to train and forecast the daily flows of the first station no: 02047500, for the Black Water River near Dendron in Virginia and the second station no: 0944200 for the Gila River near Clifton in Arizona. The feed forward network is trained using the conventional back propagation learning algorithm with many variations in the NN inputs. We explored models built using various historical data. The selection process of various architectures and training data sets for the proposed NN models are presented. A comparative study of both ANN and the conventional Auto-Regression (AR model networks indicates that the artificial neural networks performed better than the AR model. Hence, we recommend ANN as a useful tool for river flow forecasting.
Recursive wind speed forecasting based on Hammerstein Auto-Regressive model
Highlights: • Developed a new recursive WSF model for 1–24 h horizon based on Hammerstein model. • Nonlinear HAR model successfully captured chaotic dynamics of wind speed time series. • Recursive WSF intrinsic error accumulation corrected by applying rotation. • Model verified for real wind speed data from two sites with different characteristics. • HAR model outperformed both ARIMA and ANN models in terms of accuracy of prediction. - Abstract: A new Wind Speed Forecasting (WSF) model, suitable for a short term 1–24 h forecast horizon, is developed by adapting Hammerstein model to an Autoregressive approach. The model is applied to real data collected for a period of three years (2004–2006) from two different sites. The performance of HAR model is evaluated by comparing its prediction with the classical Autoregressive Integrated Moving Average (ARIMA) model and a multi-layer perceptron Artificial Neural Network (ANN). Results show that the HAR model outperforms both the ARIMA model and ANN model in terms of root mean square error (RMSE), mean absolute error (MAE), and Mean Absolute Percentage Error (MAPE). When compared to the conventional models, the new HAR model can better capture various wind speed characteristics, including asymmetric (non-gaussian) wind speed distribution, non-stationary time series profile, and the chaotic dynamics. The new model is beneficial for various applications in the renewable energy area, particularly for power scheduling
Non-contact video-based vital sign monitoring using ambient light and auto-regressive models.
Tarassenko, L; Villarroel, M; Guazzi, A; Jorge, J; Clifton, D A; Pugh, C
2014-05-01
Remote sensing of the reflectance photoplethysmogram using a video camera typically positioned 1 m away from the patient's face is a promising method for monitoring the vital signs of patients without attaching any electrodes or sensors to them. Most of the papers in the literature on non-contact vital sign monitoring report results on human volunteers in controlled environments. We have been able to obtain estimates of heart rate and respiratory rate and preliminary results on changes in oxygen saturation from double-monitored patients undergoing haemodialysis in the Oxford Kidney Unit. To achieve this, we have devised a novel method of cancelling out aliased frequency components caused by artificial light flicker, using auto-regressive (AR) modelling and pole cancellation. Secondly, we have been able to construct accurate maps of the spatial distribution of heart rate and respiratory rate information from the coefficients of the AR model. In stable sections with minimal patient motion, the mean absolute error between the camera-derived estimate of heart rate and the reference value from a pulse oximeter is similar to the mean absolute error between two pulse oximeter measurements at different sites (finger and earlobe). The activities of daily living affect the respiratory rate, but the camera-derived estimates of this parameter are at least as accurate as those derived from a thoracic expansion sensor (chest belt). During a period of obstructive sleep apnoea, we tracked changes in oxygen saturation using the ratio of normalized reflectance changes in two colour channels (red and blue), but this required calibration against the reference data from a pulse oximeter. PMID:24681430
DONG Ming
2008-01-01
As a new maintenance method, CBM (condition based maintenance) is becoming more and more important for the health management of complicated and costly equipment. A prerequisite to widespread deployment of CBM technology and prac-tice in industry is effective diagnostics and prognostics. Recently, a pattern recog-nition technique called HMM (hidden Markov model) was widely used in many fields. However, due to some unrealistic assumptions, diagnositic results from HMM were not so good, and it was difficult to use HMM directly for prognosis. By relaxing the unrealistic assumptions in HMM, this paper presents a novel approach to equip-ment health management based on auto-regressive hidden semi-Markov model (AR-HSMM). Compared with HMM, AR-HSMM has three advantages: 1)It allows explicitly modeling the time duration of the hidden states and therefore is capable of prognosis. 2) It can relax observations' independence assumption by accom-modating a link between consecutive observations. 3) It does not follow the unre-alistic Markov chain's memoryless assumption and therefore provides more pow-erful modeling and analysis capability for real problems. To facilitate the computation in the proposed AR-HSMM-based diagnostics and prognostics, new forwardbackward variables are defined and a modified forward-backward algorithm is developed. The evaluation of the proposed methodology was carried out through a real world application case study: health diagnosis and prognosis of hydraulic pumps in Caterpillar Inc. The testing results show that the proposed new approach based on AR-HSMM is effective and can provide useful support for the decision-making in equipment health management.
Gani, Abdullah; Mohammadi, Kasra; Shamshirband, Shahaboddin; Khorasanizadeh, Hossein; Seyed Danesh, Amir; Piri, Jamshid; Ismail, Zuraini; Zamani, Mazdak
2016-08-01
The availability of accurate solar radiation data is essential for designing as well as simulating the solar energy systems. In this study, by employing the long-term daily measured solar data, a neural network auto-regressive model with exogenous inputs (NN-ARX) is applied to predict daily horizontal global solar radiation using day of the year as the sole input. The prime aim is to provide a convenient and precise way for rapid daily global solar radiation prediction, for the stations and their immediate surroundings with such an observation, without utilizing any meteorological-based inputs. To fulfill this, seven Iranian cities with different geographical locations and solar radiation characteristics are considered as case studies. The performance of NN-ARX is compared against the adaptive neuro-fuzzy inference system (ANFIS). The achieved results prove that day of the year-based prediction of daily global solar radiation by both NN-ARX and ANFIS models would be highly feasible owing to the accurate predictions attained. Nevertheless, the statistical analysis indicates the superiority of NN-ARX over ANFIS. In fact, the NN-ARX model represents high potential to follow the measured data favorably for all cities. For the considered cities, the attained statistical indicators of mean absolute bias error, root mean square error, and coefficient of determination for the NN-ARX models are in the ranges of 0.44-0.61 kWh/m2, 0.50-0.71 kWh/m2, and 0.78-0.91, respectively.
Non-contact video-based vital sign monitoring using ambient light and auto-regressive models
Remote sensing of the reflectance photoplethysmogram using a video camera typically positioned 1 m away from the patient’s face is a promising method for monitoring the vital signs of patients without attaching any electrodes or sensors to them. Most of the papers in the literature on non-contact vital sign monitoring report results on human volunteers in controlled environments. We have been able to obtain estimates of heart rate and respiratory rate and preliminary results on changes in oxygen saturation from double-monitored patients undergoing haemodialysis in the Oxford Kidney Unit. To achieve this, we have devised a novel method of cancelling out aliased frequency components caused by artificial light flicker, using auto-regressive (AR) modelling and pole cancellation. Secondly, we have been able to construct accurate maps of the spatial distribution of heart rate and respiratory rate information from the coefficients of the AR model. In stable sections with minimal patient motion, the mean absolute error between the camera-derived estimate of heart rate and the reference value from a pulse oximeter is similar to the mean absolute error between two pulse oximeter measurements at different sites (finger and earlobe). The activities of daily living affect the respiratory rate, but the camera-derived estimates of this parameter are at least as accurate as those derived from a thoracic expansion sensor (chest belt). During a period of obstructive sleep apnoea, we tracked changes in oxygen saturation using the ratio of normalized reflectance changes in two colour channels (red and blue), but this required calibration against the reference data from a pulse oximeter. (paper)
Gani, Abdullah; Mohammadi, Kasra; Shamshirband, Shahaboddin; Khorasanizadeh, Hossein; Seyed Danesh, Amir; Piri, Jamshid; Ismail, Zuraini; Zamani, Mazdak
2015-06-01
The availability of accurate solar radiation data is essential for designing as well as simulating the solar energy systems. In this study, by employing the long-term daily measured solar data, a neural network auto-regressive model with exogenous inputs (NN-ARX) is applied to predict daily horizontal global solar radiation using day of the year as the sole input. The prime aim is to provide a convenient and precise way for rapid daily global solar radiation prediction, for the stations and their immediate surroundings with such an observation, without utilizing any meteorological-based inputs. To fulfill this, seven Iranian cities with different geographical locations and solar radiation characteristics are considered as case studies. The performance of NN-ARX is compared against the adaptive neuro-fuzzy inference system (ANFIS). The achieved results prove that day of the year-based prediction of daily global solar radiation by both NN-ARX and ANFIS models would be highly feasible owing to the accurate predictions attained. Nevertheless, the statistical analysis indicates the superiority of NN-ARX over ANFIS. In fact, the NN-ARX model represents high potential to follow the measured data favorably for all cities. For the considered cities, the attained statistical indicators of mean absolute bias error, root mean square error, and coefficient of determination for the NN-ARX models are in the ranges of 0.44-0.61 kWh/m2, 0.50-0.71 kWh/m2, and 0.78-0.91, respectively.
A new data integration approach for AutoCAD and GIS
Ye, Hongmei; Li, Yuhong; Wang, Cheng; Li, Lijun
2006-10-01
GIS has its advantages both on spatial data analysis and management, particularly on the geometric and attributive information management, which has also attracted lots attentions among researchers around world. AutoCAD plays more and more important roles as one of the main data sources of GIS. Various work and achievements can be found in the related literature. However, the conventional data integration from AutoCAD to GIS is time-consuming, which also can cause the information loss both in the geometric aspects and the attributive aspects for a large system. It is necessary and urgent to sort out new approach and algorithm for the efficient high-quality data integration. In this paper, a novel data integration approach from AutoCAD to GIS will be introduced based on the spatial data mining technique through the data structure analysis both in the AutoCAD and GIS. A practicable algorithm for the data conversion from CAD to GIS will be given as well. By a designed evaluation scheme, the accuracy of the conversion both in the geometric and the attributive information will be demonstrated. Finally, the validity and feasibility of the new approach will be shown by an experimental analysis.
Integrated Multiscale Latent Variable Regression and Application to Distillation Columns
Muddu Madakyaru
2013-01-01
Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.
Support vector regression for the solution of linear integral equations
The aim of this paper is to establish a support vector regression method for semi-discrete ill-posed problems. We consider the equation Af = g, where a linear integral operator A is known; discrete measurements of the right-hand side are observed and a solution f* is sought. For the reconstruction, instead of a standard square loss function, Vapnik's ε-intensive function is used to measure the distance between Af and g. This avoids an overfitting to disturbed data and guarantees additional stability given that the cut-off parameter ε is chosen appropriately. The resulting solution procedure can be formulated as a quadratic program. Besides the method, a Sobolev error analysis and a parameter strategy for the regularization parameters are provided. The results are substantiated with a numerical example
Integrated lens auto-focus system driven by a nut-type ultrosonic motor (USM)
ZHOU TieYing; CHEN Yu; LU CunYue; FU DeYong; HU XiaoPing; LI Yi; TIANBin
2009-01-01
This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image sensor, and a driver IC of the motor. The sizes of the AF (auto-focus) module are 8.5 mm×8.5 mm×5.9 mm. The piezoelectric elements are bonded on the external surface of the stator. The rotor has external screw thread that engages with the inner screw thread of the stator. When the pie-zoelectric elements are excited by the driver IC, a bend traveling wave in plane is generated on the stator along the circle direction, that drives the lens rotor to rotate and then to move axially. The driver IC is controlled by an image feedback of an image sensor centered on the axis of the casing, then the optical focusing is realized. The power consumption is zero at rest and is less than 0.25 W in motion; focusing precision 3 r/s(180 r/min); response <10 ms; high reliability: resistant to shock and fall off; directly driven by the driver IC without transmission mechanism; the friction force is namely the driving force and noiseless. The integrated optical auto-focus system is very useful, espe-cially for cellular phones. The image resolution of 3-5 MP has been obtained in the module prototypes of the cellular phone.
Integrated lens auto-focus system driven by a nut-type ultrosonic motor (USM)
无
2009-01-01
This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image sensor, and a driver IC of the motor. The sizes of the AF (auto-focus) module are 8.5 mm×8.5 mm×5.9 mm. The piezoelectric elements are bonded on the external surface of the stator. The rotor has external screw thread that engages with the inner screw thread of the stator. When the piezoelectric elements are excited by the driver IC, a bend traveling wave in plane is generated on the stator along the circle direction, that drives the lens rotor to rotate and then to move axially. The driver IC is controlled by an image feedback of an image sensor centered on the axis of the casing, then the optical focusing is realized. The power consumption is zero at rest and is less than 0.25 W in motion; focusing precision <10 μm; speed >3 r/s(180 r/min); response <10 ms; high reliability: resistant to shock and fall off; directly driven by the driver IC without transmission mechanism; the friction force is namely the driving force and noiseless. The integrated optical auto-focus system is very useful, especially for cellular phones. The image resolution of 3―5 MP has been obtained in the module prototypes of the cellular phone.
Biyanto, Totok R.
2016-06-01
Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO2 emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.
We describe the design, fabrication and test results of a segmented hybrid photon detector with integrated auto-triggering front-end electronics. Both the photodetector and its VLSI readout electronics are custom designed and have been tailored to the requirements of a recently proposed novel geometrical concept of a positron emission tomograph. Emphasis is put on the PET-specific features of the device. The detector has been fabricated in the photocathode facility at CERN
Gregor, Karol; Danihelka, Ivo; Mnih, Andriy; Blundell, Charles; Wierstra, Daan
2013-01-01
We introduce a deep, generative autoencoder capable of learning hierarchies of distributed representations from data. Successive deep stochastic hidden layers are equipped with autoregressive connections, which enable the model to be sampled from quickly and exactly via ancestral sampling. We derive an efficient approximate parameter estimation method based on the minimum description length (MDL) principle, which can be seen as maximising a variational lower bound on the log-likelihood, with ...
An Auto sequence Code to Integrate a Neutron Unfolding Code with thePC-MCA Accuspec
In a neutron spectrometry using proton recoil method, the neutronunfolding code is needed to unfold the measured proton spectrum to become theneutron spectrum. The process of the unfolding neutron in the existingneutron spectrometry which was successfully installed last year was doneseparately. This manuscript reports that the auto sequence code to integratethe neutron unfolding code UNFSPEC.EXE with the software facility of thePC-MCA Accuspec has been made and run successfully so that the new neutronspectrometry become compact. The auto sequence code was written based on therules in application program facility of PC-MCA Accuspec and then it wascompiled using AC-EXE. Result of the test of the auto sequence code showedthat for binning width 20, 30, and 40 giving a little different spectrumshape. The binning width around 30 gives a better spectrum in mean of givingsmall error compared to the others. (author)
Christensen, Bent Jesper; Kruse, Robinson; Sibbertsen, Philipp
We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of fractional...
Integrating the gamma spectrum auto-analysis program with elemental analysis software by k-zero method is the objective for many researchers. This work is the first stepin building an auto analysis program of gamma spectrum, which includes modules of reading spectrum, displaying spectrum, calibrating energy of peak, smoothing spectrum, calculating peak area and determining content of elements in sample. Then, the results from the measurements of standard samples by a low level spectrometer using HPGe detector are compared to those of other gamma spectrum auto-analysis programs. (author)
The auto propane industry began in Canada in the 1980s as a result of government policies favoring alternate fuels. Total propane demand is ca 4.1 billion liters, with over 30% of this demand in the automotive fuel market. This market is concentrated in Ontario, British Columbia, and Alberta. The total number of propane-powered vehicles in Canada is ca 140,000, the number of propane service stations is over 5,000, and there are ca 850 shops where automobiles can be converted to run on propane. The number of conversions was 15,000 in 1992, down from nearly 23,000 in 1991. The cost of conversion ranges from $1,500 to $2,000. The advantages of propane over gasoline is lower emissions, notably in cold weather, and good performance. To maintain propane's environmental advantage, initiatives are being led by the Canadian Auto Propane Council to develop a multifaceted technical strategy. This strategy includes cooperation with the auto industry to encourage original equipment manufacture of a propane car, participation in gaseous and liquid fuel injection projects designed to permit vehicle conversion, introduction of a stand-alone automatic stop fill valve to eliminate emissions in the filling process, and research on conversion of medium- and heavy-duty engines. Cooperation with the industry in the USA is also recommended
... 5 Things to Know About Zika & Pregnancy Auto Safety KidsHealth > For Parents > Auto Safety Print A A ... by teaching some basic rules. Importance of Child Safety Seats Using a child safety seat (car seat) ...
An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains of pairs of cells are obtained from an improvement of the adiabatic approximation introduced previously by Moreno-Bote and Parga [Phys. Rev. Lett. 92, 028102 (2004)]. These two functions define the firing variability and firing synchronization between neurons, and are of much importance for understanding neuron communication
Auto Adjusting Astronomical Telescope
Rohit R. Ghalsasi; Prof. N. D. Dhoot
2014-01-01
Astronomical telescope is powerful and basic tool for star or celestial observation. Here we proposed integrated system using Raspberry Pi for auto adjusting astronomical telescope. This integrated circuit helps to control stellar monitoring, stellar targeting, and tracking functions of telescope. Astro compass gives the direction of the celestial objects.
Auto Adjusting Astronomical Telescope
Rohit R. Ghalsasi
2014-04-01
Full Text Available Astronomical telescope is powerful and basic tool for star or celestial observation. Here we proposed integrated system using Raspberry Pi for auto adjusting astronomical telescope. This integrated circuit helps to control stellar monitoring, stellar targeting, and tracking functions of telescope. Astro compass gives the direction of the celestial objects.
无
2010-01-01
China counts on developing new-energy vehicles to maintain its auto-market leadership While it remains to be seen what kind of progress will be made following the UN Climate Conference in Cancun, Mexico,
Control of integrating process with dead time using auto-tuning approach
G. Saravanakumar
2009-03-01
Full Text Available A modification of Smith predictor for controlling higher order processes with integral action and long dead-time is proposed in this paper. The controller used in this Smith predictor is an Integral-Proportional Derivative controller, where the Integrator is in the forward path and the Proportional and Derivative control are in the feedback, acting on the feedback signal. The main objective of this paper is to design a dead time compensator, which has minimum tuning parameters, simple controller tuning, and robust performance of tuning formulae, and to obtain a critically damped system that is as fast as possible in its set point and load disturbance rejection performance. The controller in this paper is tuned by an adaptive method. This paper also presents a survey of various dead time compensators and their performance analysis.
Díaz, S.; Deferrari, G.; Martinioni, D.; Oberto, A.
2000-05-01
Factors affecting UV radiation at the earth's surface include the solar zenith angle, earth-sun distance, clouds, aerosols, altitude, ozone and the ground's albedo. The variation of some factors, such as solar zenith angle and earth-sun distance, is well established. Total column ozone and UV radiation are inversely related, but the presence of clouds may affect the resulting UV in such a way that a depletion in the total column ozone may not always lead to an increase in the radiation at the earth's surface. The aim of this paper is to determine the contribution to the variation of the biologically effective irradiance by geometric factors, clouds and ozone, jointly and separately, in Ushuaia (54°49'S, 68°19'W, sea level), and the seasonal variation of this relationship, given the magnitude and seasonal distribution of the ozone depletion and the frequent presence of high cloud cover in this site. For this purpose, multivariate and simple regression analyses of daily and monthly integrated irradiances weighted by the DNA damage action spectrum as a function of total column ozone and the integrated irradiances in the band 337-342 nm (as a proxy for cloud cover and geometric factors) have been performed. For the analysed period (September 1989-December 1996) more than 97% of the variation of the DNA damage weighted daily integrated irradiances is described by changes in ozone, clouds and geometric factors. Simple regression analysis for daily integrated irradiances, grouped by month, shows that most of this variation is explained by clouds and geometric factors, except in spring, when strong ozone depletion occurs intermittently over this area. When monthly trends are removed, similar results are observed, except for late winter.
Integrated product and process system with continuous improvement in the auto parts industry
I.B. Silva; G.F. Batalha; M. Stipkovik Filho; F.Z. Ceccarelli; J.B. Anjos; M. Fesz
2009-01-01
Purpose: Quality systems (QS) update must be based on the enterprise organization to assure customer satisfaction, as Deming, Juran and Feigenbaum did in their time, to seek improvement processes to reach high quality performance. This way, the proposal of this paper is the development of quality system integration model of product and process with continuous improvement.Design/methodology/approach: To reach this goal, a Brazilian automotive parts quality system was improved through the Compu...
Integrated product and process system with continuous improvement in the auto parts industry
I.B. Silva
2009-06-01
Full Text Available Purpose: Quality systems (QS update must be based on the enterprise organization to assure customer satisfaction, as Deming, Juran and Feigenbaum did in their time, to seek improvement processes to reach high quality performance. This way, the proposal of this paper is the development of quality system integration model of product and process with continuous improvement.Design/methodology/approach: To reach this goal, a Brazilian automotive parts quality system was improved through the Computer Integrated Manufacturing (CIM, Design for Manufacturing and Assembly (DFMA and Lean Six Sigma (LSS methodologies.Findings: The paper shows what the problems are during the factory quality system management. The results achieved in the studied company show the performance quality evolution through their indicators.Research limitations/implications: The article presents quality system problems of only one Brazilian plant of an automotive industry.Practical implications: Presented in this article should be a way to look for continuous improvement methods.Originality/value: The paper is supported on the authors’ practical experiences to improve the quality system at a Brazilian plant.
In this work a compact catalytic reactor was analysed for the ATR of CH4 as natural gas surrogate. Structured catalysts (commercial honeycomb and foam monoliths) performances in CH4 processing were studied. In reactor design, great attention has been paid to the thermal integration, in order to obtain a total self-sustainability of the process avoiding additional external heat sources, and improving the plant compactness. Through a heat exchange system integrated in the reactor, water and air streams are preheated by exploiting the heat from exhaust stream, allowing to feed reactants at room temperature as well as cooling products stream at a temperature suitable for further purification stages (Water Gas Shift, Preferential Oxidation). In order to have a very comprehensive process analysis, temperatures and composition were monitored in 6 point along the catalytic bed. The influence of catalytic system geometry and thermal conductivity in the process performances were also analysed. Preliminary tests showed high thermal system efficiency, with a good hydrocarbon conversion at different operating conditions for both catalyst typologies
XU Jing; YANG Chi; ZHANG Guoping
2007-01-01
Information model is adopted to integrate factors of various geosciences to estimate the susceptibility of geological hazards. Further combining the dynamic rainfall observations, Logistic regression is used for modeling the probabilities of geological hazard occurrences, upon which hierarchical warnings for rainfall-induced geological hazards are produced. The forecasting and warning model takes numerical precipitation forecasts on grid points as its dynamic input, forecasts the probabilities of geological hazard occurrences on the same grid, and translates the results into likelihoods in the form of a 5-level hierarchy. Validation of the model with observational data for the year 2004 shows that 80% of the geological hazards of the year have been identified as "likely enough to release warning messages". The model can satisfy the requirements of an operational warning system, thus is an effective way to improve the meteorological warnings for geological hazards.
Real-time regression schemes for integrating measurements with emergency response predictions
If real-time radiological measurements are available, current computer technology provides an opportunity for improving hazard predictions during an emergency. The potential for substantially reducing prediction uncertainties by integrating real-time observations and predictions into an automated emergency response system exists. In developing such a system, great care must be taken to properly balance prediction-model sophistication, data quality and timing, response time, and a data/model integration scheme. The Atmospheric Release Advisory Capability (ARAC) of the U.S. Department of Energy has initiated a program to establish the feasibility of incorporating an automated, real-time method of correcting predictions using radiological measurements acquired during an emergency. This Predictor/Corrector (P/C) Model is predicated on (1) being able to obtain real-time measurements, (2) having a sophisticated prediction model capable of running many times during an emergency response and, (3) using an appropriately designed non-linear regression scheme. Model sophistication will be designed as a function of available response time. The current plan is to use ARAC's MATHEW/ADPIC model as the P/C predictor, but with the model restructured with multiple loops to provide differing degrees of sophistication, to be invoked as response time allows. We study different regression schemes potentially appropriate for the Predictor/Corrector Model. We use the ARAC Instantaneous Point Source (IPS) model to predict observations that were made at the Savannah River Plant for SF6 tracer releases during 1983. The number of IPS runs and the range of the initial parameter guesses that result in acceptable predictions are determined. Recommendations are made of the best candidates for implementation in the MATHEW/ADPIC model
This book starts introduction of conception, application system, software for CAD, function of Auto CAD, kinds and function of Auto CAD files. It deals with starting of Auto CAD, dialogue box and Auto CAD interface, utility command, 2D drawing command, check command, control system, dimension, hatching command, layer command, block, 3D drawing, plotting and printing, auto CAD and application of data, supply program of auto CAD, AME and region modeler, EDLIN, script optimization of Auto CAD and composition on demand.
Jokar Arsanjani, J.; Helbich, M.; Kainz, W.; Boloorani, A.
2013-01-01
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-eco
National Aeronautics and Space Administration — The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to...
PENG, JIE; Zhu, Ji; Bergamaschi, Anna; Han, Wonshik; Noh, Dong-Young; Pollack, Jonathan R; Wang, Pei
2010-01-01
In this paper, we propose a new method remMap -- REgularized Multivariate regression for identifying MAster Predictors -- for fitting multivariate response regression models under the high-dimension-low-sample-size setting. remMap is motivated by investigating the regulatory relationships among different biological molecules based on multiple types of high dimensional genomic data. Particularly, we are interested in studying the influence of DNA copy number alterations on RNA transcript level...
Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approach with temperature variant parameter. The proposed work forecasts the future load demand correlation with linear and non-linear parameters (i.e. considering temperature in our case) through different regression approaches. The overall load forecasting error is 2.98% which is very much acceptable. From proposed regression techniques, Quadratic Regression technique performs better compared to than other techniques because it can optimally fit broad range of functions and data sets. The work proposed in this paper, will pave a path to effectively forecast the specific day load with multiple variance factors in a way that optimal accuracy can be maintained. (author)
Lima, Maria Luisa Pedroso; Sim-Sim, Margarida
2004-01-01
Elegendo-se como assunto o auto-conceito e mais especificamente o auto-conceito sexual, procura-se um aprofundamento teórico do tema. Desenvolve-se a definição do auto-conceito e auto-conceito sexual, suas perspectivas historicas, natureza, estrutura e fontes que veiculam a sua construção. São descritos alguns modelos teóricos de auto-conceito e auto-conceito sexual diferenciando entre modelos unidimensionais e multidimensionais. Analisa-se o recente constructo de auto-conceito sexual sublinh...
Irfan Ahmed Halepoto; Muhammad Aslam Uqaili; Bhawani Shanker Chowdhry
2014-01-01
Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approac...
Herrera Fernanda G
2013-01-01
Full Text Available Abstract Background Whole pelvis intensity modulated radiotherapy (IMRT is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. Purpose To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB regression and motion during chemo-radiotherapy (CRT for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. Methods and materials Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM was used to evaluate the degree of motion. The Dice’s similarity coefficient (DSC was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. Results The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction
Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice’s similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. The CTV-SIB had important
An integrated approach to analyze strategy map using BSC – FUZZY AHP: A case study of auto industry
Mohammad Abdolshah
2012-04-01
Full Text Available In an environment, which is highly competitive and everything changes rapidly, managers of organizations face with problems such as how to identify important factors preventing organizations from optimum use of available resources and capacities and invest more on key factors. To achieve this goal, we need to develop an effective strategy map for organizations. The strategy map is a constructional and expanding procedure to identify relationships among all the organization's strategic goals, which play a key role in achieving competitive advantage. Undoubtedly, representing a model to identify and to evaluate the important items for each of available goals in strategy map of each organization is a significant help for management to access higher competition benefits. In this paper, strategic objectives in the strategy map of one of the best producer of electric auto part makers in Iran called Electric Vehicle Co. East are evaluated based on balanced score card perspective and to assign appropriate values to available factors we use a hybrid method consist of AHP technique with Fuzzy logic.
Biological brain tumor imaging using O-(2-[18F]fluoroethyl)-L-tyrosine (FET)-PET combined with inverse treatment planning for locally restricted dose escalation in patients with glioblastoma multiforme seems to be a promising approach. The aim of this study was to compare inverse with forward treatment planning for an integrated boost dose application in patients suffering from a glioblastoma multiforme, while biological target volumes are based on FET-PET and MRI data sets. In 16 glioblastoma patients an intensity-modulated radiotherapy technique comprising an integrated boost (IB-IMRT) and a 3-dimensional conventional radiotherapy (3D-CRT) technique were generated for dosimetric comparison. FET-PET, MRI and treatment planning CT (P-CT) were co-registrated. The integrated boost volume (PTV1) was auto-contoured using a cut-off tumor-to-brain ratio (TBR) of ≥ 1.6 from FET-PET. PTV2 delineation was MRI-based. The total dose was prescribed to 72 and 60 Gy for PTV1 and PTV2, using daily fractions of 2.4 and 2 Gy. After auto-contouring of PTV1 a marked target shape complexity had an impact on the dosimetric outcome. Patients with 3-4 PTV1 subvolumes vs. a single volume revealed a significant decrease in mean dose (67.7 vs. 70.6 Gy). From convex to complex shaped PTV1 mean doses decreased from 71.3 Gy to 67.7 Gy. The homogeneity and conformity for PTV1 and PTV2 was significantly improved with IB-IMRT. With the use of IB-IMRT the minimum dose within PTV1 (61.1 vs. 57.4 Gy) and PTV2 (51.4 vs. 40.9 Gy) increased significantly, and the mean EUD for PTV2 was improved (59.9 vs. 55.3 Gy, p < 0.01). The EUD for PTV1 was only slightly improved (68.3 vs. 67.3 Gy). The EUD for the brain was equal with both planning techniques. In the presented planning study the integrated boost concept based on inversely planned IB-IMRT is feasible. The FET-PET-based automatically contoured PTV1 can lead to very complex geometric configurations, limiting the achievable mean dose in the boost
Giovanni Angiulli
2012-01-01
Full Text Available The design of Substrate Integrated Waveguide (SIW resonators is usually a cumbersome process, especially due to the length âtrial and errorâ procedure involved in this task. In this study Support Vector Regression Machines (SVRMs are employed to compensate the modeling errors associated to the design of SIW rectangular cavity resonators. To validate the proposed approach, we have compared the design outputs provided by our method with the results provided by commercial full wave software. The comparison between our predictions and the full wave simulations validate the effectiveness of the proposed approach.
Integrative analysis of multiple diverse omics datasets by sparse group multitask regression
Lin, Dongdong; Zhang, Jigang; Li, Jingyao; He, Hao; Deng, Hong-Wen; Wang, Yu-Ping
2014-01-01
A variety of high throughput genome-wide assays enable the exploration of genetic risk factors underlying complex traits. Although these studies have remarkable impact on identifying susceptible biomarkers, they suffer from issues such as limited sample size and low reproducibility. Combining individual studies of different genetic levels/platforms has the promise to improve the power and consistency of biomarker identification. In this paper, we propose a novel integrative method, namely spa...
Boundary integral equation method calculations of surface regression effects in flame spreading
Altenkirch, R. A.; Rezayat, M.; Eichhorn, R.; Rizzo, F. J.
1982-01-01
A solid-phase conduction problem that is a modified version of one that has been treated previously in the literature and is applicable to flame spreading over a pyrolyzing fuel is solved using a boundary integral equation (BIE) method. Results are compared to surface temperature measurements that can be found in the literature. In addition, the heat conducted through the solid forward of the flame, the heat transfer responsible for sustaining the flame, is also computed in terms of the Peclet number based on a heated layer depth using the BIE method and approximate methods based on asymptotic expansions. Agreement between computed and experimental results is quite good as is agreement between the BIE and the approximate results.
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
This book explains Auto CAD easily, which introduces improved function in Auto CAD R 13, such as direct import and export of 3 DS pile, revised render order structure, and explanations of assist, view Draw, construct and modify. Next it gives descriptions of Auto CAD conception, application and system. The last part deals with line, arc, circle, ellipse, erase, undo, redo, redraw, line type, multi line, limits, zoom, move, copy, rotate, array, mirror, grid, snap, units, offset and poly line.
Razana Alwee; Siti Mariyam Hj Shamsuddin; Roselina Sallehuddin
2013-01-01
Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated m...
Salin, Franck
2010-01-01
AutoBin is an Excel Macro written in Microsoft Visual Basic (VBA). It automatically analyzes raw data generated from microsatellites genotyping software such as STRand (Toonen et al., 2001) or GeneMapper (Applied Biosystems, USA). AutoBin has been developed by Franck Salin. It can deal with unlimited number of loci and samples, with no consideration of the type of SSRs motifs. AutoBin helps the user to bin his data with visual alerts and format automatically the data for downstream analysis.
Metherell, Phil
1989-01-01
AutoCAD Workbook helps new users learn the basics of AutoCad, providing guidance on most of the commonly used functions in which the program operates.This book discusses loading AutoCad and starting a drawing; drawing and erasing lines, circles, and arcs; and setting up the drawing environment. The topics on drawing and editing polylines; entering text and text styles; and layers, linetype, and color are also considered. This publication likewise covers creating and using blocks, hatching and extracting information, dimensioning drawings, 3D visualization, and plotting a drawing. Other
Alenius, Minna
2013-01-01
Tämä opinnäytetyö toimii AutoPalinin messukonseptina tapahtumamarkkinoinnissa. Messukonseptissa käsitellään AutoPalinin osallistumista yleisömessuille sekä messuilla tapahtuvaa markkinointia. Opinnäytetyössä kerrotaan yleisesti messuista tärkeänä ja vahvana mediana sekä vaiheittain messuprojektin etenemisen ja tarpeelliset työvaiheet suunnittelusta aina messujen jälkeen tehtäviin osioihin, jotka kaikki yhdessä oikein toteutettuna mahdollistavat AutoPalinille parhaan mahdollisen messumenestyks...
Halfaoui, Nadia
2015-01-01
Les hépatites auto –immun sont d’une atteinte inflammatoire aigu ou chronique du foie caractérisé par réaction immunitaire dirigé contre un antigène de hôte .il en existe deux types : Hépatite auto immun type 1 : caractérisé par présence d’auto anticorps anti muscle lisse de spécifité antiactine, anticorps anti nucléaires. Type 2 caractérisé par présence d’auto anticorps anti microsome de foie et de rein (anti LMNK1). Leur étiologies est multifactoriel ; impliquant...
Tagaotsitav "Auto" / Kristiina Vaarik
Vaarik, Kristiina
2001-01-01
Chris O'Connelli "Auto" Vanemuises, lavastaja Mark Babych. Etendusele tegid muusika ansamblist Bizarre tuntud muusikud Tristan Priimägi ja Lauri Liivak, kes artiklis sellest räägivad. Esietendus 2. detsembril 2000
Hao, Lingxin
2007-01-01
Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao
Larsen, Klaus; Merlo, Juan
2005-01-01
The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic regression model has been extended to allow for correlated responses by introducing random effects. However......, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure of...... regression. For this purpose, the authors propose an odds ratio measure, the interval odds ratio, that takes these difficulties into account. The authors demonstrate the two measures by investigating heterogeneity between neighborhoods and effects of neighborhood-level covariates in two examples...
This book has introduction to use this book and explanation of application on Auto CAD, which includes, sub directories, batch files, robot wrist, design of standard paper, title block, robort weld room, robert wrist joint, PC board, plant sym, electro, PID, machines, robots, bubbles, plant, schema, Pid, plant assembly, robots, dim plant, PL-ASSM, plotting line weight control, symbol drawing joint, Auto CAD using script file, set up of workout · MNU, workout MNU, ACAD, LSP and workout · MNU.
Bailey, D H; Williams, S [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Chame, J; Chen, C; Hall, M [USC/ISI, Marina del Rey, CA 90292 (United States); Dongarra, J; Moore, S; Seymour, K; You, H [University of Tennessee, Knoxville, TN 37996 (United States); Hollingsworth, J K; Tiwari, A [University of Maryland, College Park, MD 20742 (United States); Hovland, P; Shin, J [Argonne National Laboratory, Argonne, IL 60439 (United States)], E-mail: mhall@isi.edu
2008-07-15
The enormous and growing complexity of today's high-end systems has increased the already significant challenges of obtaining high performance on equally complex scientific applications. Application scientists are faced with a daunting challenge in tuning their codes to exploit performance-enhancing architectural features. The Performance Engineering Research Institute (PERI) is working toward the goal of automating portions of the performance tuning process. This paper describes PERI's overall strategy for auto-tuning tools and recent progress in both building auto-tuning tools and demonstrating their success on kernels, some taken from large-scale applications.
Jensen, Henrik
1998-01-01
I 1998 var AutoCAD Arkitektskolens basale CAD-tilbud til de studerende. Kursets vægt ligger på konstruktion og strukturering af 3d-modeller og med udgangspunkt i dette, 2d-tegning. Kurset er opbygget over CAD Clasic skabelonen (se min forskning). Kompendiet kan bruges til selvstudium.......I 1998 var AutoCAD Arkitektskolens basale CAD-tilbud til de studerende. Kursets vægt ligger på konstruktion og strukturering af 3d-modeller og med udgangspunkt i dette, 2d-tegning. Kurset er opbygget over CAD Clasic skabelonen (se min forskning). Kompendiet kan bruges til selvstudium....
The enormous and growing complexity of today's high-end systems has increased the already significant challenges of obtaining high performance on equally complex scientific applications. Application scientists are faced with a daunting challenge in tuning their codes to exploit performance-enhancing architectural features. The Performance Engineering Research Institute (PERI) is working toward the goal of automating portions of the performance tuning process. This paper describes PERI's overall strategy for auto-tuning tools and recent progress in both building auto-tuning tools and demonstrating their success on kernels, some taken from large-scale applications
Kahane, Leo H
2007-01-01
Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics. New to the Second Edition Offers greater coverage of simple panel-data estimation:
World Auto Parts Market Thriving
无
2007-01-01
@@ In a global market with increased competition, the global auto industrial chain in some regions of Europe, the U.S. and Japan is transforming into a new relationship between the auto parts producers and complete vehicle producers.
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
Lorentzen, Jochen; Robbins, Glen; Barnes, Justin
2004-01-01
The paper describes the formation of the Durban Auto Cluster in the context of trade liberalization. It argues that the improvement of operational competitiveness of firms in the cluster is prominently due to joint action. It tests this proposition by comparing the gains from cluster activities i...
2009-01-01
Ongevallen waarbij auto's in diep water of in een sloot of greppel belanden zijn dikwijls gecompliceerd en lopen vaak ernstig af. Gezien deze afloop en het feit dat ongeveer de helft van de overleden bij dit soort ongevallen niet omkomt door verdrinking maar door verwondingen, zijn preventieve maatr
WANG PEI
2006-01-01
@@ "Facing a very good market space at the present time,no matter domestic or overseas,we are increasing all the resources we can to expand our production capacity,"says Xu Peng,sales manager of a major Chinese private auto parts company."However,there are still many external conditions restricting the expansion."
McFarlane, Bob
2002-01-01
New features in AutoCAD 2002 are covered in this book, making it a useful refresher course for anyone using AutoCAD at this level, and upgrading to the new software release. The material in the book is also relevant to anyone using other recent releases, including, AutoCAD 2000.
AutoCAD 2014 and AutoCAD LT 2014
Gladfelter, Donnie
2013-01-01
A step-by-step tutorial introduction to AutoCAD As the only book to teach AutoCAD using a continuous tutorial which allows you to follow along sequentially or jump in at any exercise by downloading the drawing files, this Autodesk Official Press book is ideal for the AutoCAD novice. Industry expert and AutoCAD guru Donnie Gladfelter walks you through the powerful features of AutoCAD, provides you with a solid foundation of the basics, and shares the latest industry standards and techniques. The hands-on tutorial project inspired by real-world workflows that runs throughout the book
Sandeep Sivanandan
2015-01-01
Agile practices are receiving considerable attention from industry as an alternative to traditional software development approaches. However, there are a number of challenges in combining Agile [2] with Test-driven development (TDD) [10] practices, cloud deployments, continuous integration (CI), non-stop performance, load, security and accessibly testing. From these challenges; Continuous Integration is a relatively an approach widely discussed and practiced in software testing. This paper de...
杨惠; 李峰
2009-01-01
为了克服粒子群算法和蚁群算法的缺陷,将改进的粒子群算法和蚁群算法进行融合,形成了PAAA算法,并将此算法应用于自主清洁机器人行为路径的仿真实验.结果表明:PAAA在求解性能上优于粒子群算法,在时间效率上优于蚁群算法.%In order to overcome the deficiencies of particle swarm optimization and ant colony algorithm,this paper integrates the improved particle swarm optimization and ant colony algorithm,formats the PAAA,this algorithm is applied to auto-cleaning robot simulation path.The results show that:PAAA superior performance in solving particle swarm optimization,in terms of time better than the ant colony algorithm efficiency.
Andersen, Michael Rye; Heinicke, Hugo
1996-01-01
Formålet med dette notat er at give en introduktion til tegning af et generalarrangement ved anvendelse af CAD-programmet AutoCAD. Generalarrangementets formål er at skabe en overskuelig præsentation af et skibsprojekt. Det skal gøres indenfor de rammer, som ligger til grund for praktiskprojekter......Formålet med dette notat er at give en introduktion til tegning af et generalarrangement ved anvendelse af CAD-programmet AutoCAD. Generalarrangementets formål er at skabe en overskuelig præsentation af et skibsprojekt. Det skal gøres indenfor de rammer, som ligger til grund for...
Lorentzen, Jochen; Robbins, Glen; Barnes, Justin
2004-01-01
The paper describes the formation of the Durban Auto Cluster in the context of trade liberalization. It argues that the improvement of operational competitiveness of firms in the cluster is prominently due to joint action. It tests this proposition by comparing the gains from cluster activities in the areas of supplier development, human resource development, logistics, and benchmarking, and by contrasting the impact of joint action against a host of other variables, notably international com...
Altahlawi, Naif
2008-01-01
This Project demonstrates a constructive approach in Jeddah, Saudi Arabia where the building would be a symbol of luxury. The auto mall gives a common platform to different car makers to display their cars and address their competition under one roof which would be convenient for customers to compare cars. The building has twelve show room units. Each unit has a display area, offices, and a service area. The roof structure system facilitates a large open span beneath it. A series of con...
This study presents a new process for valorisation of black liquor into gases that are used to reduce ZnO and promote zinc nanosheet synthesis, besides energy generation. During the black liquor pyrolysis and auto-gasification, gases evolve, especially carbon monoxide, and promote ZnO reduction with Zn(v) release. The metal is condensed yielding zinc nanosheets, with partial surface re-oxidation in presence of carbon dioxide. The process was investigated at the micro scale using thermal analyses (TG/DTG/DTA) and the gases evolved were analysed by FTIR spectroscopy (TG/FTIR). The process was also studied in laboratory scale using a tubular electric furnace. The black liquor/ZnO mixture was placed at the quartz tube and the sample was heated to 900 °C at 10 °C/min, and the temperature was held at 900 °C for 1 h. The nanostructures growth was catalyst-free, without pressure reduction or a template, at temperatures lower than those required in the classical carbothermal reduction of ZnO with fossil carbon. The nanostructures were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and infrared spectroscopy (FTIR). One mechanism was presented in an attempt to explain the synthesis of Zn/ZnO nanosheets that are crystalline. This green and innovative process has potential use at the industry due to its operational conditions, low costs and technological importance of Zn and ZnO nanostructures. -- Graphical abstract: Display Omitted Highlights: ► Black liquor and ZnO mixture were submitted to a heat treatment until 900 °C. ► The black liquor suffered pyrolysis and auto-gasification. ► ZnO is reduced by CO yielding Znv, that is condensed generating Zn/ZnO nanosheets. ► The nanostructures are characterized and a mechanism of reactions is presented. ► The new process can produce energy and nanostructures in large scale.
Huang, Dong; Cabral, Ricardo; De la Torre, Fernando
2016-02-01
Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose estimation from images. These methods typically map image features ( X) to continuous (e.g., pose) or discrete (e.g., object category) values. A major drawback of existing discriminative methods is that samples are directly projected onto a subspace and hence fail to account for outliers common in realistic training sets due to occlusion, specular reflections or noise. It is important to notice that existing discriminative approaches assume the input variables X to be noise free. Thus, discriminative methods experience significant performance degradation when gross outliers are present. Despite its obvious importance, the problem of robust discriminative learning has been relatively unexplored in computer vision. This paper develops the theory of robust regression (RR) and presents an effective convex approach that uses recent advances on rank minimization. The framework applies to a variety of problems in computer vision including robust linear discriminant analysis, regression with missing data, and multi-label classification. Several synthetic and real examples with applications to head pose estimation from images, image and video classification and facial attribute classification with missing data are used to illustrate the benefits of RR. PMID:26761740
AutoCAD / AutoCAD LT 2014 fundamentals metric
ASCENT center for technical knowledge
2014-01-01
The objective of AutoCAD/AutoCAD LT 2014 Fundamentals is to enable students to create a basic 2D drawing in the AutoCAD software. Even at this fundamental level, the AutoCAD software is one of the most sophisticated computer applications that you are likely to encounter. Therefore learning to use it can be challenging. To make the process easier and provide flexibility for instructors and students, the training guide is divided into two parts that can be taken independently.
Internet与AutoCAD%Internet and AutoCAD
李岩; 修立刚
2009-01-01
从Internet是国际上交流信息最重要的方法出发,介绍了AutoCAD的网络功能.即如何在Web上发布图形和在AutoCAD中进行网上的图形操作.%Is internationally exchanges the information most important method from Intemet to embark, introduced the AutoCAD network function, how namely on Web to issue that the graph and carries in-line graph operation in AutoCAD.
Ji Zhou
2014-06-01
Full Text Available The land surface temperature (LST is one of the most important parameters of surface-atmosphere interactions. Methods for retrieving LSTs from satellite remote sensing data are beneficial for modeling hydrological, ecological, agricultural and meteorological processes on Earth’s surface. Many split-window (SW algorithms, which can be applied to satellite sensors with two adjacent thermal channels located in the atmospheric window between 10 μm and 12 μm, require auxiliary atmospheric parameters (e.g., water vapor content. In this research, the Heihe River basin, which is one of the most arid regions in China, is selected as the study area. The Moderate-resolution Imaging Spectroradiometer (MODIS is selected as a test case. The Global Data Assimilation System (GDAS atmospheric profiles of the study area are used to generate the training dataset through radiative transfer simulation. Significant correlations between the atmospheric upwelling radiance in MODIS channel 31 and the other three atmospheric parameters, including the transmittance in channel 31 and the transmittance and upwelling radiance in channel 32, are trained based on the simulation dataset and formulated with three regression models. Next, the genetic algorithm is used to estimate the LST. Validations of the RM-GA method are based on the simulation dataset generated from in situ measured radiosonde profiles and GDAS atmospheric profiles, the in situ measured LSTs, and a pair of daytime and nighttime MOD11A1 products in the study area. The results demonstrate that RM-GA has a good ability to estimate the LSTs directly from the MODIS data without any auxiliary atmospheric parameters. Although this research is for local application in the Heihe River basin, the findings and proposed method can easily be extended to other satellite sensors and regions with arid climates and high elevations.
This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies
"Chinese Style" Auto marketing Thrives
无
2007-01-01
@@ Over the past 10 years, China's auto industry has seen rapid growth.The miracle of such fast development, from a humble beginning to a strong player in the world's auto industry,can be attributed to a variety of factors.The most important factor, however, is that the auto industry has incorporated Chinese characteristics during its growth,whether facing challenges or developing new innovations.
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Brilliance Auto: Chinese, Global, Successful
无
2004-01-01
As the only automobile sponsor of BOAO FORUM FOR ASIA in April 2004, Brilliance Auto had a great opportunity to show her 'New Zhonghua" sedan which is an upper-medium car with completely independent intellectual property rights and repre sents the independent development philosophy of Brilliance Auto and is especially made for business personnel. The development pattern of Zhonghua sedan set a brand new model in Chinese auto industry to utilize the global resources and talents and international division of labor in the international arena, and she has become a typical sample of independent brand sedans in the contemporary Chinese auto industry.……
This book introduces Auto CAD 14, which includes summary of basic things of Auto CAD 14, user interface for Auto CAD, basic drawing and advice, layer and set-up drawing, drawing with Auto CAD tools exactly, basic drawing of every thing, edit command, control of display, modeling and view ports of drawing space, various things drawing, writing letters, modification of floor plan, and check, block, X ref, lines and hatch, writing measurement, floor plan and OLE exchange of data, 3D floor plan, and rendering and presentation.
McFarlane, Bob
2005-01-01
Beginning AutoCAD 2005 is a course based on learning and practising the essentials of 2D drawing using AutoCAD. Bob McFarlane's hands-on approach is uniquely suited to independent learning and use on courses. The focus on 2D drawing in one book, ensures the reader gets a thorough grounding in the subject, with a greater depth of coverage than tends to be available from general introductions to AutoCAD. As a result, this book provides a true, step-by-step, detailed exploration of the AutoCAD functions required at each stage of producing a 2D drawing - an approach often
van Gerven, Nicole Mf; de Boer, Ynto S; Mulder, Chris Jj; van Nieuwkerk, Carin Mj; Bouma, Gerd
2016-05-21
To provide an update of the latest trends in epidemiology, clinical course, diagnostics, complications and treatment of auto immune hepatitis (AIH). A search of the MEDLINE database was performed using the search terms: "auto immune hepatitis", "clinical presentation", "symptoms", "signs", "diagnosis", "auto antibodies", "laboratory values", "serology", "histopathology", "histology", "genetics", "HLA genes", "non-HLA genes", "environment", "epidemiology", "prevalence", "incidence", "demographics", "complications", "HCC", "PBC", "PSC", "corticosteroid", "therapy", "treatment", "alternative treatment". English-language full-text articles and abstracts were considered. Articles included reviews, meta-analysis, prospective retrospective studies. No publication date restrictions were applied. AIH is an immune meditated progressive inflammatory liver disease that predominantly affects middle-aged females but may affect people of all ages. The clinical spectrum of AIH is wide, ranging from absent or mild symptoms to fulminant hepatic failure. The aetiology of AIH is still unknown, but is believed to occur as the consequence of an aberrant immune response towards an un-known trigger in a genetically susceptible host. In the absence of a gold standard, diagnosis is based on the combination of clinical, biochemical and histopathological criteria. Immunosuppressive treatment has been the cornerstone of treatment since the earliest description of the disease in 1950 by Waldenström. Such treatment is often successful at inducing remission and generally leads to normal life expectancy. Nevertheless, there remain significant areas of unmet aetiological a clinical needs including fundamental insight in disease pathogenesis, optimal therapy, duration of treatment and treatment alternatives in those patients unresponsive to standard treatment regimens. PMID:27217697
van Gerven, Nicole MF; de Boer, Ynto S; Mulder, Chris JJ; van Nieuwkerk, Carin MJ; Bouma, Gerd
2016-01-01
To provide an update of the latest trends in epidemiology, clinical course, diagnostics, complications and treatment of auto immune hepatitis (AIH). A search of the MEDLINE database was performed using the search terms: “auto immune hepatitis”, “clinical presentation”, “symptoms”, “signs”, “diagnosis”, “auto antibodies”, “laboratory values”, “serology”, “histopathology”, “histology”, “genetics”, “HLA genes”, “non-HLA genes”, “environment”, “epidemiology”, “prevalence”, “incidence”, “demographics”, “complications”, “HCC”, “PBC”, “PSC”, “corticosteroid”, “therapy”, “treatment”, “alternative treatment”. English-language full-text articles and abstracts were considered. Articles included reviews, meta-analysis, prospective retrospective studies. No publication date restrictions were applied. AIH is an immune meditated progressive inflammatory liver disease that predominantly affects middle-aged females but may affect people of all ages. The clinical spectrum of AIH is wide, ranging from absent or mild symptoms to fulminant hepatic failure. The aetiology of AIH is still unknown, but is believed to occur as the consequence of an aberrant immune response towards an un-known trigger in a genetically susceptible host. In the absence of a gold standard, diagnosis is based on the combination of clinical, biochemical and histopathological criteria. Immunosuppressive treatment has been the cornerstone of treatment since the earliest description of the disease in 1950 by Waldenström. Such treatment is often successful at inducing remission and generally leads to normal life expectancy. Nevertheless, there remain significant areas of unmet aetiological a clinical needs including fundamental insight in disease pathogenesis, optimal therapy, duration of treatment and treatment alternatives in those patients unresponsive to standard treatment regimens. PMID:27217697
Lamontagne, Frédéric; Desnoyers, Nichola; Doucet, Michel; Côté, Patrice; Gauvin, Jonny; Anctil, Geneviève; Tremblay, Mathieu
2015-09-01
In a typical optical system, optical elements usually need to be precisely positioned and aligned to perform the correct optical function. This positioning and alignment involves securing the optical element in a holder or mount. Proper centering of an optical element with respect to the holder is a delicate operation that generally requires tight manufacturing tolerances or active alignment, resulting in costly optical assemblies. To optimize optical performance and minimize manufacturing cost, there is a need for a lens mounting method that could relax manufacturing tolerance, reduce assembly time and provide high centering accuracy. This paper presents a patent pending lens mounting method developed at INO that can be compared to the drop-in technique for its simplicity while providing the level of accuracy close to that achievable with techniques using a centering machine (usually innovative auto-centering method is based on the use of geometrical relationship between the lens diameter, the lens radius of curvature and the thread angle of the retaining ring. The autocentering principle and centering test results performed on real optical assemblies are presented. In addition to the low assembly time, high centering accuracy, and environmental robustness, the INO auto-centering method has the advantage of relaxing lens and barrel bore diameter tolerances as well as lens wedge tolerances. The use of this novel lens mounting method significantly reduces manufacturing and assembly costs for high performance optical systems. Large volume productions would especially benefit from this advancement in precision lens mounting, potentially providing a drastic cost reduction.
Razana Alwee
2013-01-01
Full Text Available Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR and autoregressive integrated moving average (ARIMA to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
The state of microbiocenosis of large intestines of rats and furae which were exposed to continuous integrated radiation has been studied in the field experiments emergency premises and in the adjacent zone of its impact
Automatic detection of AutoPEEP during controlled mechanical ventilation
Nguyen Quang-Thang
2012-06-01
Full Text Available Abstract Background Dynamic hyperinflation, hereafter called AutoPEEP (auto-positive end expiratory pressure with some slight language abuse, is a frequent deleterious phenomenon in patients undergoing mechanical ventilation. Although not readily quantifiable, AutoPEEP can be recognized on the expiratory portion of the flow waveform. If expiratory flow does not return to zero before the next inspiration, AutoPEEP is present. This simple detection however requires the eye of an expert clinician at the patient’s bedside. An automatic detection of AutoPEEP should be helpful to optimize care. Methods In this paper, a platform for automatic detection of AutoPEEP based on the flow signal available on most of recent mechanical ventilators is introduced. The detection algorithms are developed on the basis of robust non-parametric hypothesis testings that require no prior information on the signal distribution. In particular, two detectors are proposed: one is based on SNT (Signal Norm Testing and the other is an extension of SNT in the sequential framework. The performance assessment was carried out on a respiratory system analog and ex-vivo on various retrospectively acquired patient curves. Results The experiment results have shown that the proposed algorithm provides relevant AutoPEEP detection on both simulated and real data. The analysis of clinical data has shown that the proposed detectors can be used to automatically detect AutoPEEP with an accuracy of 93% and a recall (sensitivity of 90%. Conclusions The proposed platform provides an automatic early detection of AutoPEEP. Such functionality can be integrated in the currently used mechanical ventilator for continuous monitoring of the patient-ventilator interface and, therefore, alleviate the clinician task.
Wind speed prediction using statistical regression and neural network
Makarand A Kulkarni; Sunil Patil; G V Rama; P N Sen
2008-08-01
Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve ﬁtting,Auto Regressive Integrated Moving Average Model (ARIMA),extrapolation with periodic function and Artiﬁcial Neural Networks (ANN)are employed to predict wind speed.These methods require wind speeds of previous hours as input.It has been found that wind speed can be predicted with a reasonable degree of accuracy using two methods,viz.,extrapolation using periodic curve ﬁtting and ANN and the other two methods are not very useful.
Lin Wu
2015-03-01
Full Text Available To better satisfy various stakeholders, firms are seeking integrated practices that can enhance their sustainability performance, also well known as the Triple Bottom Line (3BL. The fashion industry exhibits potential conflicts with the spirit of sustainability because of the waste created by high levels of demand uncertainty and the extant usage of resources in production. Literature suggests that selected stand-alone practices of lean, green, and Corporate Social Responsibility (CSR management systems have a positive impact on firm sustainability performance. However, how the combination of selected practices from these three management systems impacts the 3BL remains unclear. Based on case studies, we build an integrated sustainable practices model incorporating the most popular lean, green, and social practices and develop propositions for future tests. Our framework suggests the implementation of integrated practices would have a stronger influence on 3BL performance than individual practice implementation.
Local Linear Regression for Data with AR Errors
Runze Li; Yan Li
2009-01-01
In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques.We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one.From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.
HOU Yuexian; HE Pilian
2005-01-01
There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-dependency (IAD) and generalized irreducible auto-dependency (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.
Ana Maria Coutinho Aleksandrowicz
2009-10-01
Full Text Available Este artigo visa apresentar bases teóricas que auxiliem o exercício da participação e da integração numa equipe interdisciplinar de pesquisadores. Para tal, num primeiro momento, delinearemos noções fundamentais do novo campo conceitual proposto, o das teorias da auto-organização dos seres vivos. Exporemos, a seguir, construtos de Henri Atlan, Jean-Pierre Dupuy e Cornelius Castoriadis relevantes para a consecução do objetivo almejado. Finalmente, sugeriremos possibilidades de passagem à prática de alguns dos princípios descritos.This article presents theoretical bases to facilitate participation and integration within an interdisciplinary research team. In order to achieve this, we will sketch fundamental notions related to the new conceptual field of self-organization of living beings. Subsequently, we will expose some ideas by Henri Atlan, Jean-Pierre Dupuy and Cornelius Castoriadis that are important to reach our objectives. Finally, we will suggest how to turn these principles into practice.
Wan, Ruoling
2015-01-01
Along with the development and strategy change of Chinese economy, an increasing number of Chinese companies tend to start their globalization via cross-border mergers and acquisitions. However, the huge cultural differences usually cause cultural conflicts, which can be great challenges and obstacles to companies who are seeking to develop overseas. Thus, in the post-merger stage, it is significant for Chinese companies to pay enough attention to cultural integration in order to improve the ...
Lin Wu; Nachiappan Subramanian; Muhammad D. Abdulrahman; Chang Liu; Kee-hung Lai; Pawar, Kulwant S.
2015-01-01
To better satisfy various stakeholders, firms are seeking integrated practices that can enhance their sustainability performance, also well known as the Triple Bottom Line (3BL). The fashion industry exhibits potential conflicts with the spirit of sustainability because of the waste created by high levels of demand uncertainty and the extant usage of resources in production. Literature suggests that selected stand-alone practices of lean, green, and Corporate Social Responsibility (CSR) manag...
Onstott, Scott
2013-01-01
Learn crucial AutoCAD tools and techniques with this Autodesk Official Press Book Quickly become productive using AutoCAD 2014 and AutoCAD LT 2014 with this full color Autodesk Official Press guide. This unique learning resource features concise, straightforward explanations and real-world, hands-on exercises and tutorials. Following a quick discussion of concepts and goals, each chapter moves on to an approachable hands-on exercise designed to reinforce real-world tactics and techniques. Compelling, full-color screenshots illustrate tutorial steps, and chapters conclude with relat
CONGRATULATIONS ON AUTO CHINA 2006
无
2006-01-01
@@ In April, China Machinery Industry Federation and Media & Press Center of CCPIT have successfully organized the China Auto International(Syria)Exhibition Tour and promoted the "walk out" strategy of Chinese independent brands.
CONGRATULATIONS ON AUTO CHINA 2006
无
2006-01-01
In April, China Machinery Industry Federation and Media & Press Center of CCPIT have successfully organized the China Auto International(Syria)Exhibition Tour and promoted the "walk out" strategy of Chinese independent brands.……
Liiketoimintasuunnitelma Auto-Roiko Ky
Roiko, Sebastian
2014-01-01
Tämän opinnäytetyön tarkoituksena oli liiketoimintasuunnitelman tekeminen toimeksiantajayritys Auto-Roiko Ky:lle. Auto-Roiko Ky on kuorma-autojen maahantuontiin erikoistunut yritys Kannuksessa, Keski-Pohjanmaalla. Tavoitteena oli toiminnan kokonaisvaltainen kehittäminen ja uusien liiketoimintamallien tarkastelu. Uusina liiketoimintoina tutkittiin henkilöautokauppaa ja polttoainejakelua. Työ toteutettiin kehittämishankkeena kvalitatiivista tutkimusmenetelmää käyttäen. Tutkimusai...
Green Project in Auto Industry
Yang Wei
2007-01-01
@@ Automobile industry in China is developing very fast,which brings great business opportunities.In 2006,China was ranked the third in the world only after the United States and Japan in terms of auto sales.As the vehicle population in China is rocketing,a series of related social problems are emerging.How to fast develop auto industfy,and at the same time,protect our lwing environment? A green project is in urgent need.
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Esposito, Carlo; Barra, Anna; Evans, Stephen G.; Scarascia Mugnozza, Gabriele; Delaney, Keith
2014-05-01
The study of landslide susceptibility by multivariate statistical methods is based on finding a quantitative relationship between controlling factors and landslide occurrence. Such studies have become popular in the last few decades thanks to the development of geographic information systems (GIS) software and the related improved data management. In this work we applied a statistical approach to an area of high landslide susceptibility mainly due to its tropical climate and geological-geomorphological setting. The study area is located in the south-east region of Brazil that has frequently been affected by flood and landslide hazard, especially because of heavy rainfall events during the summer season. In this work we studied a disastrous event that occurred on January 11th and 12th of 2011, which involved Região Serrana (the mountainous region of Rio de Janeiro State) and caused more than 5000 landslides and at least 904 deaths. In order to produce susceptibility maps, we focused our attention on an area of 93,6 km2 that includes Nova Friburgo city. We utilized two different multivariate statistic methods: Logistic Regression (LR), already widely used in applied geosciences, and Random Forest (RF), which has only recently been applied to landslide susceptibility analysis. With reference to each mapping unit, the first method (LR) results in a probability of landslide occurrence, while the second one (RF) gives a prediction in terms of % of area susceptible to slope failure. With this aim in mind, a landslide inventory map (related to the studied event) has been drawn up through analyses of high-resolution GeoEye satellite images, in a GIS environment. Data layers of 11 causative factors have been created and processed in order to be used as continuous numerical or discrete categorical variables in statistical analysis. In particular, the logistic regression method has frequent difficulties in managing numerical continuous and discrete categorical variables
Liang, Hao; Gao, Lian; Liang, Bingyu; Huang, Jiegang; Zang, Ning; Liao, Yanyan; Yu, Jun; Lai, Jingzhen; Qin, Fengxiang; Su, Jinming; Ye, Li; Chen, Hui
2016-01-01
Background Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease. Methods The autoregressive integrated moving average (ARIMA) model and the generalized regression neural network (GRNN) model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention) from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and mean square error (MSE), were used to compare the performance among the three models. Results The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2)(1,1,1)12 model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models. Conclusions The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County. PMID:27258555
AutoCAD 2015 and AutoCAD LT 2015
Gladfelter, Donnie
2014-01-01
Learn AutoCAD by example with this tutorial-based guide from Autodesk Official Press Whether you are just starting out or an experienced user wanting to brush up on your skills, this Autodesk Official Press book provides you with concise explanations, focused examples, and step-by-step instructions through a hands-on tutorial project that runs throughout the book. As you progress through the project, the book introduces you to the Microsoft Windows-based AutoCAD interface and then guides you through basic commands and creating drawings. A downloadable file is available from the website so that
Auto-Generated Semantic Processing Services
Davis, Rodney; Hupf, Greg
2009-01-01
Auto-Generated Semantic Processing (AGSP) Services is a suite of software tools for automated generation of other computer programs, denoted cross-platform semantic adapters, that support interoperability of computer-based communication systems that utilize a variety of both new and legacy communication software running in a variety of operating- system/computer-hardware combinations. AGSP has numerous potential uses in military, space-exploration, and other government applications as well as in commercial telecommunications. The cross-platform semantic adapters take advantage of common features of computer- based communication systems to enforce semantics, messaging protocols, and standards of processing of streams of binary data to ensure integrity of data and consistency of meaning among interoperating systems. The auto-generation aspect of AGSP Services reduces development time and effort by emphasizing specification and minimizing implementation: In effect, the design, building, and debugging of software for effecting conversions among complex communication protocols, custom device mappings, and unique data-manipulation algorithms is replaced with metadata specifications that map to an abstract platform-independent communications model. AGSP Services is modular and has been shown to be easily integrable into new and legacy NASA flight and ground communication systems.
Byrnes, David
2009-01-01
AutoCAD is the hot computer-aided design software known for both its powerful tools and its complexity. AutoCAD 2010 for Dummies is the bestselling guide that walks you through this complicated program so you can build complex 3D technical drawings, edit like a pro, enter new dimensions, and plot with style. AutoCAD 2010 for Dummies helps you navigate the program, use the AutoCAD Design Center, create a basic layout and work with dimension, and put your drawings on the Internet. You'll soon be setting up the AutoCAD environment, using the AutoCAD Ribbon, creating annotation and dimension drawi
Laso, Emilio Aristides de Fez
2013-01-01
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a Packt Instant How-to guide, which provides concise and clear recipes for getting started with AutoIt.Instant AutoIt Scripting Essentials How-to is for beginners who wish to know more about automation and programming, system administration developers who intent to automate/manage clusters and servers, and for computer programmers who want to control any PC to create seamless automation apps.
Footprints of China Auto Internatienal Exhibition Tour
无
2008-01-01
@@ November 2008,the Sixth China Auto International(Algeria & Egypt)Exhibition Tour is ready.Since the first session was held in 1995,the Chinese auto enterprises have been to Vietnam,Cambodia,Syria,and Russian.
Tumbling Auto Import and Export
Yantai Chen
2009-01-01
@@ The seemingly rebound global financial crisis has seriously eroded world economy from 2008,of which China's tumbling auto imports and exports business is a good example.At the beginning of 2008 it kicked off as an excellent year for the Chinese automotive market,but ended with the onset of a recession in last quarter both from the perspective of import and export.
Environment-friendly Auto Marketing
无
2007-01-01
@@ Domestic auto sales have developed quickly with private vehicles making up the highest proportion, but lately customers have begun to care more about environmental protection. Therefore, the last few years has seen more and more consumption disputes and civil lawsuits resulting from the pollution inside vehicles.
Auto executives:Worried While Being Happy
无
2009-01-01
Xu Liuping,director of the board of Chang'an Auto Group,had just come back from Japan and north America before the opening of this year's Shanghai auto show.He knew something about the financial crisis towards the overseas auto industry from reports and during this trip
The New Breakthroughs of Chinese Auto Industry
Sun Yongjian
2006-01-01
@@ Auto Engine Systems: A Key Part for Reform Prof. Ouyang Minggao, Tsinghua University: The road of development from a large production country to a strong technology country eyed. By 2020, China is predicted to be the largest auto manufactuer in the world.In the view of the development of the global auto market, the fastest development is taking place in developing countries.
2006 Chinese Government Auto Purchase Forum
无
2006-01-01
Sponsored by Economic Daily and the China Machinery Enterprises Management Association, the 2006 Chinese Government Auto Purchase Forum will be held in Tianjin on July 11-13. This represents another high-level dialogue and exchange between the government and the auto industry hot on the heels of the 2005 Chinese Government Auto Purchase Forum. This event is launched to promote
Johansen, Søren
2008-01-01
The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...... eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results...
Semiparametric regression during 2003–2007
Ruppert, David
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
Byrnes, David
2007-01-01
A gentle, humorous introduction to this fearsomely complex software that helps new users start creating 2D and 3D technical drawings right awayCovers the new features and enhancements in the latest AutoCAD version and provides coverage of AutoCAD LT, AutoCAD''s lower-cost siblingTopics covered include creating a basic layout, using AutoCAD DesignCenter, drawing and editing, working with dimensions, plotting, using blocks, adding text to drawings, and drawing on the InternetAutoCAD is the leading CAD software for architects, engineers, and draftspeople who need to create detailed 2D and 3D tech
张小平
2010-01-01
在长期使用AutoCAD绘图和AutoCAD教学中,发现AutoCAD中出现的问题很多,因此给我们带来困扰和使用的不便,大降低了工作的效率.为了方便AutoCAD绘图的使用和教学,笔者提出了自己的一些高效管理AutoCAD图形,提高绘图效率的方法.
AutoCAD platform customization autolisp
Ambrosius, Lee
2014-01-01
Customize and personalize programs built on the AutoCAD platform AutoLISP is the key to unlocking the secrets of a more streamlined experience using industry leading software programs like AutoCAD, Civil 3D, Plant 3D, and more. AutoCAD Platform Customization: AutoLISP provides real-world examples that show you how to do everything from modifying graphical objects and reading and setting system variables to communicating with external programs. It also features a resources appendix and downloadable datasets and customization examples-tools that ensure swift and easy adoption. Find out how to r
Fane, Bill
2013-01-01
Find your way around AutoCAD 2014 with this full-color, For Dummies guide!Put away that pencil and paper and start putting the power of AutoCAD 2014 to work in your CAD projects and designs. From setting up your drawing environment to using text, dimensions, hatching, and more, this guide walks you through AutoCAD basics and provides you with a solid understanding of the latest CAD tools and techniques. You'll also benefit from the full-color illustrations that mirror exactly what you'll see on your AutoCAD 2014 screen and highlight the importance of AutoCAD's Mode
Contractive De-noising Auto-encoder
Chen, Fu-qiang; Wu, Yan; Zhao, Guo-dong; Zhang, Jun-Ming; Zhu, Ming; Bai, Jing
2013-01-01
Auto-encoder is a special kind of neural network based on reconstruction. De-noising auto-encoder (DAE) is an improved auto-encoder which is robust to the input by corrupting the original data first and then reconstructing the original input by minimizing the reconstruction error function. And contractive auto-encoder (CAE) is another kind of improved auto-encoder to learn robust feature by introducing the Frobenius norm of the Jacobean matrix of the learned feature with respect to the origin...
AutoCAD platform customization VBA
Ambrosius, Lee
2015-01-01
Boost productivity and streamline your workflow with expert AutoCAD: VBA programming instruction AutoCAD Platform Customization: VBA is the definitive guide to personalizing AutoCAD and the various programs that run on the AutoCAD platform, including AutoCAD Architecture, Civil 3D, Plant 3D, and more. Written by an Autodesk insider with years of customization and programming experience, this book features detailed discussions backed by real-world examples and easy-to-follow tutorials that illustrate each step in the personalization process. Readers gain expert guidance toward managing layout
Lee, Myung Hee; Liu, Yufeng
2013-12-01
The continuum regression technique provides an appealing regression framework connecting ordinary least squares, partial least squares and principal component regression in one family. It offers some insight on the underlying regression model for a given application. Moreover, it helps to provide deep understanding of various regression techniques. Despite the useful framework, however, the current development on continuum regression is only for linear regression. In many applications, nonlinear regression is necessary. The extension of continuum regression from linear models to nonlinear models using kernel learning is considered. The proposed kernel continuum regression technique is quite general and can handle very flexible regression model estimation. An efficient algorithm is developed for fast implementation. Numerical examples have demonstrated the usefulness of the proposed technique. PMID:24058224
诸良富
2009-01-01
为了解决景东县深化集体林权制度主体改革中时间紧、任务重、技术难度大、技术力量弱等实际问题,将GPS与CASS6.0、AutoCAD软件综合运用,使得外业工作速度加快,质量提高,每个技术员从一天只能勘查10～20宗林地提高到30～50宗林地,并且节省了人力、资金和时间,资料规范整齐,实现无纸化办公,档案管理方便.%In order to solve the actual problems in deepening the reform of collective forest property right system concerning critical time, heaven task, difficult technique, and poor technical ability, the software GPS and CASS6.0 as well as AutoCAD are comprehensively utilized to make the fieldwork fast speed and high quality. A technician can survey 30- 50 clans per day instead of original 10- 20 clans per day in detail. Moreover, the utilization can save human force, fund and time, and obtain standard materials to realize doing office work with no- paper and convenient file management as a result
Kılıç, Selim
2013-01-01
Linear regression is an approach to modeling the association between a numeric dependent variable y and one or more independent variables denoted X. The case of one explanatory variable in regression model is called simple linear regression. For more than one explanatory variable, then the model is called multiple linear regression. The dependent variable should be a numeric variable in linear regression. It is recommended at least 10 times as many cases as the number of independent variables...
Averaged extreme regression quantile
Jureckova, Jana
2015-01-01
Various events in the nature, economics and in other areas force us to combine the study of extremes with regression and other methods. A useful tool for reducing the role of nuisance regression, while we are interested in the shape or tails of the basic distribution, is provided by the averaged regression quantile and namely by the average extreme regression quantile. Both are weighted means of regression quantile components, with weights depending on the regressors. Our primary interest is ...
Purchasing The American Auto Industry
无
2009-01-01
Afalling giant is still huge There are reports that American Big Three are going to shut down 59 plants in this January to hold more cash for a supporting hand from the government. From the viewpoint of accountant practice and investment bank,it is the best time for local car producers to go abroad."Trapped American auto industry is much devalued and it is the best time for local producers
AutoCAD platform customization user interface, AutoLISP, VBA, and beyond
Ambrosius, Lee
2015-01-01
Take control of AutoCAD to boost the speed, quality, and precision of your work Senior drafters and savvy users are increasingly taking AutoCAD customization out of the hands of system administrators, and taking control of their own workflow. In AutoCAD Platform Customization, Autodesk customization guru Lee Ambrosius walks you through a multitude of customization options using detailed tutorials and real-world examples applicable to AutoCAD, AutoCAD LT, Civil 3D, Plant 3D, and other programs built on the AutoCAD platform. By unleashing the full power of the software, you'll simplify and str
从AutoCAD到AutoCAD Mechanical的平滑过渡
黄皓
2014-01-01
AutoCAD Mechanical是AutoCAD面向机械行业的专业版，在行业内对AutoCAD具有全面优势。在2010版的环境下，阐述了AutoCAD Mechanical的新增功能、使用优势和操作技术，可以在较短时间内实现从AutoCAD到AutoCAD Mechanical使用的平滑过渡，实现工作效率与创新能力的倍增。
Stability of the AutoQUANT (ADAC) package: filter choices
Full text: Functional assessment of the left ventricle is an integral part of the overall gated myocardial SPECT evaluation. Interpretation of perfusion images is to some extent subjective with varied preferences regarding the degree of smoothing and background subtraction. In this study we compare the functional parameters reported by the AutoQUANT (ADAC) package following processing of the raw data with five different default filters. 18 Sets of gated SPECT data were reconstructed using five different filters at the default settings. The filters used were Butterworth (Freq 0.55, order 5), Gaussian (0.55, 5), Hanning (0.55), Hamming (0.55) and Parzen (0.55). The reconstructed data was analysed using the AutoQUANT package and parameters for ejection fraction, wall motion and wall thickening were analysed. No significant difference was found in the functional parameters as reported by the AutoQUANT package using different reconstruction filters. The maximum absolute variation in the parameters was as follows: LVEF 3%, Wall Motion 0.7mm and Wall Thickening 5%. The AutoQuant package is stable in its reporting of the myocardial functional parameters regardless of the filters applied during the reconstruction of the raw data. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc
Logistics Optimization of Auto Parts Supplier Embedded by Service Alliance
Yue LONG
2013-10-01
Full Text Available To study the logistics service optimization of auto parts suppliers in China, this paper proposes a logistics service optimization model of many service enterprises to one supplier. This model which takes two logistics service enterprises and one supplier as research objects includes the enterprise interests growth model based on the Lotka-Volterra model and interests distribution model using Shapley value method amended by the contribution factor. Furthermore, an example is given to testify the model. The results show that the auto parts supplier’s logistics can be improved and cost can be reduced if the logistics service alliance was established successfully with one core integrating service enterprise and a total logistics service solution was provided. The results also show that as the cost reduces, the interests of the alliance increase and the rational distribution by the integrating service enterprise will help promote the interests of all members
AutoMoDe - Model-Based Development of Automotive Software
Ziegenbein, Dirk; Freund, Ulrich; Bauer, Andreas; Romberg, Jan; Schatz, Bernhard
2011-01-01
This paper describes first results from the AutoMoDe (Automotive Model-Based Development) project. The overall goal of the project is to develop an integrated methodology for model-based development of automotive control software, based on problem-specific design notations with an explicit formal foundation. Based on the existing AutoFOCUS framework, a tool prototype is being developed in order to illustrate and validate the key elements of our approach.
Auto-JacoBin: Auto-encoder Jacobian Binary Hashing
Fu, Xiping; McCane, Brendan; Mills, Steven; Albert, Michael; Szymanski, Lech
2016-01-01
Binary codes can be used to speed up nearest neighbor search tasks in large scale data sets as they are efficient for both storage and retrieval. In this paper, we propose a robust auto-encoder model that preserves the geometric relationships of high-dimensional data sets in Hamming space. This is done by considering a noise-removing function in a region surrounding the manifold where the training data points lie. This function is defined with the property that it projects the data points nea...
Methodische Verkenning Zelfrijdende Auto's en Bereikbaarheid
Snelder, M.; Van Arem, B.; Hoogendoorn, R.G.; Van Nes, R.
2015-01-01
De verwachting is dat de zelfrijdende auto op termijn gaat bijdragen aan het verbeteren van de doorstroming, de verkeersveiligheid en de leefbaarheid. Zodra de zelfrijdende auto een substantiële trend is, wordt deze meegenomen in de afwegingen voor nieuwe infrastructuur, onder andere via de Nationale Markt en Capaciteits-Analyse (NMCA). Om hier klaar voor te zijn is een verkenning uitgevoerd naar de manier waarop de bereikbaarheids- en doorstromingseffecten van zelfrijdende auto's met het LMS...
Auto-encoders: reconstruction versus compression
Ollivier, Yann
2014-01-01
We discuss the similarities and differences between training an auto-encoder to minimize the reconstruction error, and training the same auto-encoder to compress the data via a generative model. Minimizing a codelength for the data using an auto-encoder is equivalent to minimizing the reconstruction error plus some correcting terms which have an interpretation as either a denoising or contractive property of the decoding function. These terms are related but not identical to those used in den...
Regression analysis by example
Chatterjee, Samprit
2012-01-01
Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded
Eberly, Lynn E
2007-01-01
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit. The special cases of regression with interactions among the variables, polynomial regression, regressions with categorical (grouping) variables, and separate slopes models are also covered. Examples in microbiology are used throughout. PMID:18450050
Brilliance Auto:Chinese, Global, Successful
无
2004-01-01
@@ As the only automobile sponsor of BOAO FORUM FOR ASIA in April 2004, Brilliance Auto had a great opportunity to show her 'New Zhonghua" sedan which is an upper-medium car with completely independent intellectual property rights and repre sents the independent development philosophy of Brilliance Auto and is especially made for business personnel. The development pattern of Zhonghua sedan set a brand new model in Chinese auto industry to utilize the global resources and talents and international division of labor in the international arena, and she has become a typical sample of independent brand sedans in the contemporary Chinese auto industry.
Giraldo, Luis G. Sanchez; Principe, Jose C.
2013-01-01
A rekindled the interest in auto-encoder algorithms has been spurred by recent work on deep learning. Current efforts have been directed towards effective training of auto-encoder architectures with a large number of coding units. Here, we propose a learning algorithm for auto-encoders based on a rate-distortion objective that minimizes the mutual information between the inputs and the outputs of the auto-encoder subject to a fidelity constraint. The goal is to learn a representation that is ...
AutoProof: Auto-active Functional Verification of Object-oriented Programs
Tschannen, Julian; Furia, Carlo A.; Nordio, Martin; Polikarpova, Nadia
2015-01-01
Auto-active verifiers provide a level of automation intermediate between fully automatic and interactive: users supply code with annotations as input while benefiting from a high level of automation in the back-end. This paper presents AutoProof, a state-of-the-art auto-active verifier for object-oriented sequential programs with complex functional specifications. AutoProof fully supports advanced object-oriented features and a powerful methodology for framing and class invariants, which make...
邬昌明
2001-01-01
由于AutoCAD自动化（Automation)没有提供执行AutoCAD命令的方法，因此在利用自动化接口对AutoCAD进行二次开发时，不能直接执行AutoCAD软件自身提供的各种命令，本文提出了一种解决此问题的办法。
Research on the Teaching Method of AutoCAD%AutoCAD教学方法研究
王梅
2012-01-01
培养学生熟练地使用AutoCAD软件是一项重要的教学内容.结合在AutoCAD课程的教学实践,运用多种教学手段,创设合适的教学环境,激发学生对AutoCAD图形设计的兴趣,多方面结合进行AutoCAD教学.
关于切换回归的集成模糊聚类算法 GFC%An Integrated Fuzzy Clustering Algorithm GFC for Switching Regressions
王士同; 江海峰; 陆宏钧
2002-01-01
已经有多个方法可用于解决切换回归问题.根据所提出的基于Newton引力定理的引力聚类算法GC,结合模糊聚类算法,进一步提出了新的集成模糊聚类算法 GFC.理论分析表明GFC 能收敛到局部最小.实验结果表明GFC在解决切换回归问题时,比标准模糊聚类算法更有效,特别在收敛速度方面.%In order to solve switching regression problems, many approaches have been investigated. In this paper, anintegrated fuzzy clustering algorithm GFC that combines gravity-based clustering algorithm GC with fuzzy clustering is presented. GC, as a new hard clustering algorithm presented here, is based on the well-known Newton's Gravity Law. The theoretic analysis shows that GFC can conve rge to a local minimum of the object function. Experimental results show that GFC for switching regression problems has better performance than standard fuzzy clustering algorithms, especially in terms of convergence speed.
Fitzenberger, Bernd; Wilke, Ralf Andreas
2015-01-01
Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights by m...... treatment of the topic is based on the perspective of applied researchers using quantile regression in their empirical work....
Variational Recurrent Auto-Encoders
Fabius, Otto; van Amersfoort, Joost R.
2014-01-01
In this paper we propose a model that combines the strengths of RNNs and SGVB: the Variational Recurrent Auto-Encoder (VRAE). Such a model can be used for efficient, large scale unsupervised learning on time series data, mapping the time series data to a latent vector representation. The model is generative, such that data can be generated from samples of the latent space. An important contribution of this work is that the model can make use of unlabeled data in order to facilitate supervised...
AutoFocus Framework Documentation
Gaspar, Graça; Morgado, Luís; Neves, Pedro
2009-01-01
The work presented in this document is part of the project "AutoFocus: Adaptive Self-Improving Multi-Agent Systems" that is being developed at the research unit LabMAg, which objective is the implementation of multi-agent systems based on autonomous entities capable of self-optimized and adaptive behaviors. The notion of autonomic computation, like other notions that also imply pro-active computation, is based on autonomous entities that actively work to achieve their objectives and have t...
Naghshpour, Shahdad
2012-01-01
Regression analysis is the most commonly used statistical method in the world. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation and will help demystify regression analysis using examples from economics and with real data to show the applications of the method. T
Gaussian Process Quantile Regression using Expectation Propagation
Boukouvalas, Alexis; Barillec, Remi; Cornford, Dan
2012-01-01
Direct quantile regression involves estimating a given quantile of a response variable as a function of input variables. We present a new framework for direct quantile regression where a Gaussian process model is learned, minimising the expected tilted loss function. The integration required in learning is not analytically tractable so to speed up the learning we employ the Expectation Propagation algorithm. We describe how this work relates to other quantile regression methods and apply the ...
Functional linear regression via canonical analysis
He, Guozhong; Wang, Jane-Ling; Yang, Wenjing; 10.3150/09-BEJ228
2011-01-01
We study regression models for the situation where both dependent and independent variables are square-integrable stochastic processes. Questions concerning the definition and existence of the corresponding functional linear regression models and some basic properties are explored for this situation. We derive a representation of the regression parameter function in terms of the canonical components of the processes involved. This representation establishes a connection between functional regression and functional canonical analysis and suggests alternative approaches for the implementation of functional linear regression analysis. A specific procedure for the estimation of the regression parameter function using canonical expansions is proposed and compared with an established functional principal component regression approach. As an example of an application, we present an analysis of mortality data for cohorts of medflies, obtained in experimental studies of aging and longevity.
AutoCAD 2015 and AutoCAD LT 2015 bible
Finkelstein, Ellen
2014-01-01
The perfect reference for all AutoCAD users AutoCAD 2015 and AutoCAD LT 2015 Bible is the book you want to have close at hand to answer those day-to-day questions about this industry-leading software. Author and Autodesk University instructor Ellen Finkelstein guides readers through AutoCAD 2015 and AutoCAD LT 2015 with clear, easy-to-understand instruction and hands-on tutorials that allow even total beginners to create a design on their very first day. Although simple and fundamental enough to be used by those new to CAD, the book is so comprehensive that even Autodesk power u
Query auto completion in information retrieval
Fei Cai
2016-01-01
Query auto completion is an important feature embedded into today's search engines. It can help users formulate queries which other people have searched for when he/she finishes typing the query prefix. Today's most sophisticated query auto completion approaches are based on the collected query logs
An Auto ranging Data Converter Implementation in FPGA
Jithin Krishnan
2013-06-01
Full Text Available A novel project is being presented here for implementation an auto ranging analog to digital converter for biomedical applications completely inside an FPGA - i.e. an all-digital analog to digital (A/D converter system. The only analog part is the auto ranging circuitry and an RC Integrator outside FPGA. The system outputs 24 bits and features a sigma delta ADC of 16 bits resolution, a range detection unit with 7 bits and a sign bit for polarity detection. The analog part of the modulator is done utilizing the LVDS transceiver in the FPGA making it a real digital one. The digital section of sigma delta ADC containing the decimation filter banks is done in a cascaded filter structure form including a CIC decimation filter, droop compensation and half-band filters. The top level module was coded using VHDL and the simulation was carried out with ModelSim and MATLAB.
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. PMID:26861909
AutoWARN - Automatic Support for the Weather Warning Service at Deutscher Wetterdienst
Reichert, B. K.
2009-09-01
The AutoWARN system integrates various meteorological products in an automated warning process with manual monitoring and decision possibilities for the forecaster. It exploits and combines observations, radar products, nowcasting products, statistical forecast products, and model forecasts of Numerical Weather Prediction. It generates and permanently updates forecast-time dependant automatic warning status proposals. The forecaster manually controls and, if necessary, modifies the automatic proposals. The generated warning status is exported to an external system outside of AutoWARN for the generation of textual and graphical warning products for customers. The development of the AutoWARN system was part of the future strategy 2006 to 2015 of the Deutscher Wetterdienst (DWD); headwords within this strategy are centralization and automation of the entire warning process. On the basis of the formerly developed system AutoMON (Automatic Monitoring and Alerting of significant Weather Events), AutoWARN is fully integrated into the meteorological workstation NinJo and is currently being evaluated by the forecasters of DWD. The project was finished in spring 2009. The presentation will focus on illuminating the concept of AutoWARN and demonstrating the currently running pre-operational version of the system at the National Warning Centre (NWC) of DWD.
AutoCAD 2008 and AutoCAD LT 2008 Bible
Finkelstein, Ellen
2011-01-01
"Whether you're new to AutoCAD or a veteran, you will undoubtedly find this book to be an excellent resource."-- Abhi Singh, AutoCAD Product Manager, Autodesk, Inc.Here's the book that makes AutoCAD approachableEven the people at Autodesk look to Ellen Finkelstein for AutoCAD training, so who better to teach you about AutoCAD 2008? This comprehensive guide brings veterans up to speed on AutoCAD updates and takes novices from the basics to programming in AutoLISP(r) and VBA. Every feature is covered in a logical order, and with the Quick Start chapter, you'll be creating drawings on your very f
AutoPyFactory: A Scalable Flexible Pilot Factory Implementation
Caballero, J.; Hover, J.; Love, P.; Stewart, G. A.
2012-12-01
The ATLAS experiment at the CERN LHC is one of the largest users of grid computing infrastructure, which is a central part of the experiment's computing operations. Considerable efforts have been made to use grid technology in the most efficient and effective way, including the use of a pilot job based workload management framework. In this model the experiment submits ‘pilot’ jobs to sites without payload. When these jobs begin to run they contact a central service to pick-up a real payload to execute. The first generation of pilot factories were usually specific to a single Virtual Organization (VO), and were bound to the particular architecture of that VO's distributed processing. A second generation provides factories which are more flexible, not tied to any particular VO, and provide new and improved features such as monitoring, logging, profiling, etc. In this paper we describe this key part of the ATLAS pilot architecture, a second generation pilot factory, AutoPyFactory. AutoPyFactory has a modular design and is highly configurable. It is able to send different types of pilots to sites and exploit different submission mechanisms and queue characteristics. It is tightly integrated with the PanDA job submission framework, coupling pilot flow to the amount of work the site has to run. It gathers information from many sources in order to correctly configure itself for a site and its decision logic can easily be updated. Integrated into AutoPyFactory is a flexible system for delivering both generic and specific job wrappers which can perform many useful actions before starting to run end-user scientific applications, e.g., validation of the middleware, node profiling and diagnostics, and monitoring. AutoPyFactory also has a robust monitoring system that has been invaluable in establishing a reliable pilot factory service for ATLAS.
AutoPyFactory: A Scalable Flexible Pilot Factory Implementation
The ATLAS experiment at the CERN LHC is one of the largest users of grid computing infrastructure, which is a central part of the experiment's computing operations. Considerable efforts have been made to use grid technology in the most efficient and effective way, including the use of a pilot job based workload management framework. In this model the experiment submits ‘pilot’ jobs to sites without payload. When these jobs begin to run they contact a central service to pick-up a real payload to execute. The first generation of pilot factories were usually specific to a single Virtual Organization (VO), and were bound to the particular architecture of that VO's distributed processing. A second generation provides factories which are more flexible, not tied to any particular VO, and provide new and improved features such as monitoring, logging, profiling, etc. In this paper we describe this key part of the ATLAS pilot architecture, a second generation pilot factory, AutoPyFactory. AutoPyFactory has a modular design and is highly configurable. It is able to send different types of pilots to sites and exploit different submission mechanisms and queue characteristics. It is tightly integrated with the PanDA job submission framework, coupling pilot flow to the amount of work the site has to run. It gathers information from many sources in order to correctly configure itself for a site and its decision logic can easily be updated. Integrated into AutoPyFactory is a flexible system for delivering both generic and specific job wrappers which can perform many useful actions before starting to run end-user scientific applications, e.g., validation of the middleware, node profiling and diagnostics, and monitoring. AutoPyFactory also has a robust monitoring system that has been invaluable in establishing a reliable pilot factory service for ATLAS.
Aldrich, John
2005-01-01
In 1922 R. A. Fisher introduced the modern regression model, synthesizing the regression theory of Pearson and Yule and the least squares theory of Gauss. The innovation was based on Fisher’s realization that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of the development of statisti...
Visualisation of Regression Trees
Brunsdon, Chris
2007-01-01
he regression tree [1] has been used as a tool for exploring multivariate data sets for some time. As in multiple linear regression, the technique is applied to a data set consisting of a contin- uous response variable y and a set of predictor variables { x 1 ,x 2 ,...,x k } which may be continuous or categorical. However, instead of modelling y as a linear function of the predictors, regression trees model y as a series of ...
Understanding logistic regression analysis
Sperandei, Sandro
2014-01-01
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...
David F. Hendry; Krolzig, Hans Martin
2004-01-01
The controversy over the selection of "growth regressions" was precipitated by some remarkably numerous "estimation" strategies, including two million regressions by Sala-i-Martin [American Economic Review (1997b) Vol. 87, pp. 178-183]. Only one regression is really needed, namely the general unrestricted model, appropriately reduced to a parsimonious encompassing, congruent representation. We corroborate the findings of Hoover and Perez [Oxford Bulletin of Economics and Statistics (2004) Vol...
Weisberg, Sanford
2005-01-01
Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: ""I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression."" -Technometrics, February 1987 ""Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis."" -American Scientist, May-June 1987
Introduction to regression graphics
Cook, R Dennis
2009-01-01
Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava
Flexible survival regression modelling
Cortese, Giuliana; Scheike, Thomas H; Martinussen, Torben
2009-01-01
time-varying effects. The introduced models are all applied to data on breast cancer from the Norwegian cancer registry, and these analyses clearly reveal the shortcomings of Cox's regression model and the need for other supplementary analyses with models such as those we present here.......Regression analysis of survival data, and more generally event history data, is typically based on Cox's regression model. We here review some recent methodology, focusing on the limitations of Cox's regression model. The key limitation is that the model is not well suited to represent time...
Aerial camera auto focusing system
Wang, Xuan; Lan, Gongpu; Gao, Xiaodong; Liang, Wei
2012-10-01
Before the aerial photographic task, the cameras focusing work should be performed at first to compensate the defocus caused by the changes of the temperature, pressure etc. A new method of aerial camera auto focusing is proposed through traditional photoelectric self-collimation combined with image processing method. Firstly, the basic principles of optical self-collimation and image processing are introduced. Secondly, the limitations of the two are illustrated and the benefits of the new method are detailed. Then the basic principle, the system composition and the implementation of this new method are presented. Finally, the data collection platform is set up reasonably and the focus evaluation function curve is draw. The results showed that: the method can be used in the Aerial camera focusing field, adapt to the aviation equipment trends of miniaturization and lightweight .This paper is helpful to the further work of accurate and automatic focusing.
Badescu, Mircea
2014-01-01
Subsurface penetration by coring, drilling or abrading is of great importance for a large number of space and earth applications. An Ultrasonic/Sonic Drill/Corer (USDC) has been in development at JPL's Nondestructive Evaluation and Advanced Actuators (NDEAA) lab as an adaptable tool for many of these applications. The USDC uses a novel drive mechanism to transform the high frequency ultrasonic or sonic vibrations of the tip of a horn into a lower frequency sonic hammering of a drill bit through an intermediate free-flying mass. The USDC device idea has been implemented at various scales from handheld drills to large diameter coring devices. A series of computer programs that model the function and performance of the USDC device were developed and were later integrated into an automated modeling package. The USDC has also evolved from a purely hammering drill to a rotary hammer drill as the design requirements increased form small diameter shallow drilling to large diameter deep coring. A synthesis of the Auto-Gopher development is presented in this paper.
Ace Auto's After-sale Adds Advantages
Yan Manman
2009-01-01
@@ In the auto market,consumers often asked a question why the same car in the European and American market is cheaper than that in China.The key to this question lies in the difference of profit chains between European & American market and Chinese market.In the mature European or American market,the portion of profit from auto sales accounting for the total profit is comparatively small,and quite a large share of profit derives from the auto's after-sale service market.
Generalizacija linija i AutoCAD Map
Vučetić, Nada; Lapaine, Miljenko
2001-01-01
The paper offers the results of original research made on the application of AutoCAD Map in line generalisation. The differences and similarities have been found out between the Douglas-Peucker method and the method of line simplification that is incorporated in AutoCAD Map. There have been also the inaccuracies found out in AutoCAD Map manual relating to the issues of buffer width and tolerance, and the line width before and after simplification. The paper gives recommendations about pseudo ...
Line Generalization and AutoCAD Map
Nada Vučetić; Miljenko Lapaine
2001-01-01
The paper offers the results of original research made on the application of AutoCAD Map in line generalisation. The differences and similarities have been found out between the Douglas-Peucker method and the method of line simplification that is incorporated in AutoCAD Map. There have been also the inaccuracies found out in AutoCAD Map manual relating to the issues of buffer width and tolerance, and the line width before and after simplification. The paper gives recommendations about pseudo ...
Miranda, Gilda Cristina Nunes de Paiva
2012-01-01
Diversos estudos sugerem uma associação entre Distúrbios Alimentares e Auto-Mutilações. A sua maioria foca principalmente a Anorexia Nervosa, deixando um vazio no que diz respeito à Bulimia Nervosa. Por outro lado, são várias as opiniões que defendem que as Auto-Mutilações ocorrem apenas em doentes com Distúrbio de Personalidade Borderline. Este trabalho de revisão visa preencher a lacuna no que diz respeito à ligação ente a Bulimia Nervosa e Comportamentos Auto-Lesivos, incluindo Comportamen...
Analisis Perancangan Sistem Informasi Penjualan pada PT. Speedline Auto Showroom
Hutabarat, Elfina Yunita
2015-01-01
This research was conductedatPT. SpeedlineAutoShowroomwhichaims to determinewhether thesalesinformationsystemonPT. SpeedlineAutoShowroomisoperating effectivelyandefficiently. Thisresearchis thedata sourcedocumentsrelated to thesale ofthe system. Collecting datathrough interviews, document studyonPT. SpeedlineAutoShowroom.The data collectedwere analyzedwithdescriptivequalitativetechniques. From theresults ofthis study indicatethat thesales information systemonPT. SpeedlineAutoShowro...
Spontaneous regression of osteochondromas
Hoshi, Manabu; Takami, Masatsugu; Hashimoto, Ryouji; Okamoto, Takashi; Yanagida, Ikuhisa; Matsumura, Akira; Noguchi, Kazuko [Yodogawa Christian Hospital, Department of Orthopaedic Surgery, Osaka (Japan)
2007-06-15
Spontaneous regression of an osteochondroma is an infrequent event. In this report, two cases with spontaneous regression of osteochondromas are presented. The first case was a solitary osteochondroma of the pedunculated type involving the right proximal humerus in a 7-year-old boy. This lesion resolved over 15 months of observation. The second case was a 3-year-old girl with multiple osteochondromatosis, in whom sessile osteochondromas of the right tibia and left fibula regressed over 33 months.The mechanism of this phenomenon is discussed with a review of previous reports. Regarding treatment, careful observation may be acceptable for typical osteochondromas, especially in young children. (orig.)
Hosmer, David W; Sturdivant, Rodney X
2013-01-01
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-
Weisberg, Sanford
2013-01-01
Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus
侯红松
2011-01-01
通过对AutoCAD多年的使用及总结,摸索出AutoCAD使用中的几点应用小技巧.本文主要介绍了AutoCAD中倒角及圆角的处理、AutoCAD表格制作、在Word文档中插入AutoCAD图形、AutoCAD图形的打印技巧及AutoCAD选择技巧六种应用技巧.
AutoCAD 2014 review for certification official certification preparation
ASCENT center for technical knowledge
2014-01-01
The AutoCAD® 2014 Review for Certification book is intended for users of AutoCAD® preparing to complete the AutoCAD 2014 Certified Professional exam. This book contains a collection of relevant instructional topics, practice exercises, and review questions from the Autodesk Official Training Guides (AOTG) from ASCENT - Center for Technical Knowledge pertaining specifically to the Certified Professional exam topics and objectives. This book is intended for experienced users of AutoCAD in preparation for certification. New users of AutoCAD should refer to the AOTG training guides from ASCENT, such as AutoCAD/AutoCAD LT 2014 Fundamentals, for more comprehensive instruction.
Development of ATSR (Auto Thermal Steam Reformer)
'Full text:' Auto-thermal reformers are used popularly for fuel cell vehicle because they are compact and can start up quickly. On the other hand, steam reformers are used for stationary fuel cell power plant because they are good thermal efficiency. While, there are many cases using the auto- thermal reformer for stationary use with expectation of cost reduction in USA, as well. However, they are still insufficient for its durability, compactness and cost. We have been developing the new type of fuel processing system that is auto-thermal steam reformer (ATSR), which is hybrid of a conventional steam reformer (STR) and a conventional auto-thermal reformer (ATR). In this study, some proto-type of ATSR for field test were designed, tried manufacturing and tested performance and durability. And we have tried to operate with fuel cell stack to evaluate the system interface performance, that is, operability and controllability. (author)
Range-Based Auto-Focus Project
National Aeronautics and Space Administration — Maracel Systems and Software Technologies, LLC proposes a revolutionary Range-Based Auto Focus (RBAF) system that will combine externally input range, such as might...
AutoCAD 2013 and AutoCAD LT 2013 bible
Finkelstein, Ellen
2012-01-01
The bestselling guide to AutoCAD, fully updated for the 2013 version AutoCAD, the number one architectural drawing software, can be challenging to learn. This comprehensive guide has sold more than 160,000 copies in previous editions and is the go-to resource for architects, engineers, drafters, interior designers, and space planners who need to learn and use AutoCAD and AutoCAD LT. From the basics of creating drawings and using commands to 2D and 3D drawing techniques, using layers, rendering, and customizing the program, this book covers it all. A Quick Start guide allows eve
AutoMap & AutoLink: Tools for Communicating Complex & DynamicData-Structures using MPI
Goujon, Delphine; Michel, Martial; Peeters, Jasper; Devaney, Judith Ellen
1998-01-01
This article describes two software tools, AutoMap and AutoLink, that facilitate the use of data-structures in MPI. AutoMap is a program that parses a file of user-defined data-structures and generates new MPI types out of basic and previously defined MPI data-types. Our software tool automatically handles specialized error checking related to memory mapping. AutoLink is an MPI library that allows the transfert of complex, dynimacally linked, and possibly heterogeneous structures through MPI....
George: Gaussian Process regression
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
NDRC Issued Opinions to Regulate Auto Industry
无
2007-01-01
@@ In view of the surplus of China's auto in dustry production capacity, and the situation may get intensified, the National Development and Reform Commission(NDRC) recently issued the implementation opinions for auto industry to deal with the surplus of production capacity, and expedite the structural adjustment based on the relevant dispose of the State Council's notice about expediting the structural adjustment of the industries with surplus production capacity.
PLC Based Hydraulic Auto Ladle System
Amogh Tayade; Anuja Chitre
2014-01-01
In this paper we have implemented a PLC based Hydraulic Auto Ladle System for Casting Department of Victory Precisions Pvt. Ltd. Chakan, Pune. This project work presents the study and design of PLC based Hydraulic Auto Ladle System. Aluminium pouring is the key process in Casting and Forging industry. Different products are manufactured by the company for automobile sector using aluminium. Programmable Logic Controller (PLC) is used for the automation of pouring process. Au...
Auto-associative nanoelectronic neural network
In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns
AutoCAD-To-NASTRAN Translator Program
Jones, A.
1989-01-01
Program facilitates creation of finite-element mathematical models from geometric entities. AutoCAD to NASTRAN translator (ACTON) computer program developed to facilitate quick generation of small finite-element mathematical models for use with NASTRAN finite-element modeling program. Reads geometric data of drawing from Data Exchange File (DXF) used in AutoCAD and other PC-based drafting programs. Written in Microsoft Quick-Basic (Version 2.0).
Computing Mass Properties From AutoCAD
Jones, A.
1990-01-01
Mass properties of structures computed from data in drawings. AutoCAD to Mass Properties (ACTOMP) computer program developed to facilitate quick calculations of mass properties of structures containing many simple elements in such complex configurations as trusses or sheet-metal containers. Mathematically modeled in AutoCAD or compatible computer-aided design (CAD) system in minutes by use of three-dimensional elements. Written in Microsoft Quick-Basic (Version 2.0).
Auto-associative nanoelectronic neural network
Nogueira, C. P. S. M.; Guimarães, J. G. [Departamento de Engenharia Elétrica - Laboratório de Dispositivos e Circuito Integrado, Universidade de Brasília, CP 4386, CEP 70904-970 Brasília DF (Brazil)
2014-05-15
In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns.
Distributed multinomial regression
Taddy, Matt
2015-01-01
This article introduces a model-based approach to distributed computing for multinomial logistic (softmax) regression. We treat counts for each response category as independent Poisson regressions via plug-in estimates for fixed effects shared across categories. The work is driven by the high-dimensional-response multinomial models that are used in analysis of a large number of random counts. Our motivating applications are in text analysis, where documents are tokenized and the token counts ...
Sparse Multivariate Factor Regression
Kharratzadeh, Milad; Coates, Mark
2015-01-01
We consider the problem of multivariate regression in a setting where the relevant predictors could be shared among different responses. We propose an algorithm which decomposes the coefficient matrix into the product of a long matrix and a wide matrix, with an elastic net penalty on the former and an $\\ell_1$ penalty on the latter. The first matrix linearly transforms the predictors to a set of latent factors, and the second one regresses the responses on these factors. Our algorithm simulta...
Xiong, Shifeng
2011-01-01
In this paper we discuss the variable selection method from \\ell0-norm constrained regression, which is equivalent to the problem of finding the best subset of a fixed size. Our study focuses on two aspects, consistency and computation. We prove that the sparse estimator from such a method can retain all of the important variables asymptotically for even exponentially growing dimensionality under regularity conditions. This indicates that the best subset regression method can efficiently shri...
RFID and Auto-ID in planning and logistics
Jones, Erick C
2011-01-01
As RFID technology is becoming increasingly popular, the need has arisen to address the challenges and approaches to successful implementation. RFID and Auto-ID in Planning and Logistics: A Practical Guide for Military UID Applications presents the concepts for students, military personnel and contractors, and corporate managers to learn about RFID and other automatic information capture technologies, and their integration into planning and logistics functions. The text includes comparisons of RFID with technologies such as bar codes, satellite tags, and global positioning systems and provides
Andreasen, Daniel; Morgenthaler Edmund, Jens; Zografos, Vasileios;
2016-01-01
. Furthermore, we use the concept of auto-context by sequentially training a number of classification forests to create and improve context features, which are finally used to train a regression forest for pCT prediction. We evaluate the pCT quality in terms of the voxel-wise error and the radiologic accuracy...
Regression versus No Regression in the Autistic Disorder: Developmental Trajectories
Bernabei, P.; Cerquiglini, A.; Cortesi, F.; D' Ardia, C.
2007-01-01
Developmental regression is a complex phenomenon which occurs in 20-49% of the autistic population. Aim of the study was to assess possible differences in the development of regressed and non-regressed autistic preschoolers. We longitudinally studied 40 autistic children (18 regressed, 22 non-regressed) aged 2-6 years. The following developmental…
New perspectives on auto propane
In spite of the high level of propane use in vehicles in North America (relative to the use of compressed natural gas (CNG) or methanol), the alternate-fuel research and development activities of original equipment manufacturers (OEMs) are focusing on methanol, CNG, and electric vehicles. If OEM indifference to propane continues, propane vehicles will continue to be available only in after-market conversions, denying propane the benefits of OEM mass-production economics, quality control, retail distribution, and other factors. Recent developments in auto propane are reported which should be considered by OEMs and policymakers to allow propane to enter the mass-scale motor vehicle market. Propane and the liquefied petroleum gas (LPG) mix used as a motor vehicle fuel are often regarded as just a byproduct of natural gas production and oil refining, giving the impression that propane/LPG will not be available in sufficient quantities to support a mass market. It is shown that LPG supply is market-responsive and that over 20 billion gal of new supply could be made available from North American sources by the year 2000 and over 27 billion gal by 2005, sufficient to supply 12.5% of the projected North American vehicle fleet in 2005. The new supply would come from incremental expansion of existing production, displacement of LPG from lower-value uses, and LPG synthesis. The environmental performance of propane/LPG engines is also compared to that of engines running on gasoline, natural gas, and methanol. Advantages of LPG over gasoline include lower carbon content and lower CO emissions, and advantages over CNG arise from the high greenhouse gas activity and long life of methane. 12 figs
邱翠榕
2012-01-01
To tackle the separation between theory and practice existing in the class of maintenance and repair ot auto electrical device, the paper proposes taking the competence-based education principle as guide, identifying the need of job market and developing a comprehensive modular-based course which integrates teaching, learning and do- ing. The experiment shows that with the integrated pedagogical model, students can quickly acquire the relevant knowl- edge and skills.%针对当前汽车检测与维修技术专业课程教学中的理论与实践分离问题,结合现代职业教育体系以能力为本位的培养思路,开发出紧贴汽车行业人才需求变化的汽车机电维修的汽车电器综合化模块课程,采用教学做一体化教学方法,通过实践,效果显著,学生能较快掌握相关知识和技能操作。
AutoCAD 2012 and AutoCAD LT 2012 Bible
Finkelstein, Ellen
2011-01-01
The latest version of this perennial favorite, in-depth, reference-tutorial This top-selling book has been updated by AutoCAD guru and author Ellen Finkelstein to provide you with the very latest coverage of both AutoCAD 2012 and AutoCAD LT 2012. It begins with a Quick Start tutorial, so you start creating right away. From there, the book covers so much in-depth material on AutoCAD that it is said that even Autodesk employees keep this comprehensive book at their desks. A DVD is included that features before-and-after drawings of all the tutorials and plenty of great examples from AutoCAD prof
Bache, Stefan Holst
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....
范付松; 胡新丽; 李长冬; 朱志明
2012-01-01
This paper adopts standard method and Seed method separately to make liquefaction evaluation about saturated sands, based on large drill data in Xiamen. Then, using generalized regression neural network, taking the data that show different evaluated results as training samples and also test samples, we carry out the second evaluation of the remained drill data. The results show that the generalized regression neural network presents a good function and a high forecast precision. In addition, this integrated evaluation method can improve the precision of sand liquefaction of saturated sands, and provide reference for the research in sand liquefaction evaluation in other places.%基于厦门地区大量钻孔试验数据,分别采用规范法和Seed法对该区饱和砂土进行液化判别.然后选取二者判别结果相同的数据作为训练和测试样本,运用广义回归神经网络,对二者判别结果分歧的钻孔数据进行二次判别.结果表明:广义回归神经网络性能良好,预测准确度高.此外,这种综合判别方法也提高了饱和砂土液化判别的准确度,并为其他地区饱和砂土的液化判别研究提供借鉴和参考.
Using AutoCAD to improve the visibility of the organizational technological design
Lebedeva Irina Mikhailovna
2014-01-01
Full Text Available The article describes the issue of increasing the visibility of technological solutions in organizational-technological design. The ability to visualize the main stages of building process technology contributes to organic integration of all the requirements. A special role for the harmonious perception is played by correct display of the lighting facilities, shadowing. Realistic shadows help to analyze the rooms’ insolation of the designed facility and the surrounding areas. We give a justification for the use of AutoCAD in order to automate the process of visualizing the results of organizational-technological design. The author describes the methods of obtaining realistic natural lighting in AutoCAD without significantly increasing the complexity of the process. Engineering companies in 46 % of cases use the software AutoCAD in order to create construction plans. AutoCAD has a variety of possibilities and is constantly evolving. Continuation is one of the benefits of this program. AutoCAD is unique in terms of customization, because, apart from instruction languages, it has two built-in programming languages: AutoLISP and VisualBasic. Because of these specific features AutoCAD allows to create any applications related to graphics implementation. Constant monitoring of lightning changes allows finding the appropriate in terms of aesthetics, ergonomics and insolation decisions on planning and associating a building or structure to the environment. Solar lighting is simulated by a combination of several directional lightning point sources. The author offers a brief description of the program algorithm, which allows automatically managing lighting settings and creating a file with a realistic visualization of the design solutions.
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models should note carefully both their models’ identifying assumptions and which causal attributions can safely be concluded from their analysis....
Multiple linear regression analysis
Edwards, T. R.
1980-01-01
Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.
Bounded Gaussian process regression
Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan
2013-01-01
We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...
AutoCAD platform customization user interface and beyond
Ambrosius, Lee
2014-01-01
Make AutoCAD your own with powerful personalization options Options for AutoCAD customization are typically the domain of administrators, but savvy users can perform their own customizations to personalize AutoCAD. Until recently, most users never thought to customize the AutoCAD platform to meet their specific needs, instead leaving it to administrators. If you are an AutoCAD user who wants to ramp up personalization options in your favorite software, AutoCAD Platform Customization: User Interface and Beyond is the perfect resource for you. Author Lee Ambrosius is recognized as a leader in Au
Luketić, Antonio; Padovan, Ivan
2011-01-01
AutoCAD Civil 3D je vrlo kompleksan i napredan program za geodeziju i građevinarstvo. Survey izbornik predstavlja mali dio tog softvera. U programu je sadržana mogućnost kreiranja vlastitih kodova kao i naredbi kojima možemo ubrzati vizualizaciju izmjerenih objekata. Njegovim korištenjem se znatno skraćuje vrijeme obrade podataka. Članak je napisan na temelju jednostavnog, ali korisnog primjera kojime smo željeli upoznati čitatelje s prilično nepoznatom aplikacijom koju nudi AutoCAD Civil 3D....
Parallel auto-correlative statistics with VTK.
Pebay, Philippe Pierre [Kitware, France; Bennett, Janine Camille
2013-08-01
This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.
Design and Field Implementation of Auto Tuned Virtual Instrumentation Corrosion Controller
Gopalakrishnan, J.; Agnihotri, Ganga; Deshpande, D. M.
2016-06-01
Corrosion in underground metallic pipeline leads to leakage which is hazardous when oil/natural gas is transported. Rate of corrosion in metal pipeline can be controlled by impressing dc current to the gas pipeline and thereby making metal pipeline to act as cathode of corrosion cell. Proportional integral controllers are used in impressed current cathodic protection application; tuning of proportional and integral constants of these controllers requires expertise. Step open, step close and relay tuning methods are compared; relay tuning provided better results for cathodic protection application. Ziegler-Nichols tuning formulas are used to select tuning parameters based on loop response. Virtual instrumentation is used for design, development, testing and field implementation of auto tuned PI controller. Proposed auto tuned proportional integral impressed current cathodic protection controller precisely controls corrosion in pipeline by selecting optimum proportional and integral constants. Controller effectiveness is cross verified using electrical resistance probe.
Ridge Regression: A Regression Procedure for Analyzing Correlated Independent Variables.
Rakow, Ernest A.
Ridge regression is presented as an analytic technique to be used when predictor variables in a multiple linear regression situation are highly correlated, a situation which may result in unstable regression coefficients and difficulties in interpretation. Ridge regression avoids the problem of selection of variables that may occur in stepwise…
Subset selection in regression
Miller, Alan
2002-01-01
Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...
Low rank Multivariate regression
Giraud, Christophe
2010-01-01
We consider in this paper the multivariate regression problem, when the target regression matrix $A$ is close to a low rank matrix. Our primary interest in on the practical case where the variance of the noise is unknown. Our main contribution is to propose in this setting a criterion to select among a family of low rank estimators and prove a non-asymptotic oracle inequality for the resulting estimator. We also investigate the easier case where the variance of the noise is known and outline that the penalties appearing in our criterions are minimal (in some sense). These penalties involve the expected value of the Ky-Fan quasi-norm of some random matrices. These quantities can be evaluated easily in practice and upper-bounds can be derived from recent results in random matrix theory.
AutoCAD 2015 and AutoCAD LT 2015 essentials
Onstott, Scott
2014-01-01
Step-by-step instructions for the AutoCAD fundamentals AutoCAD 2015 Essentials contains 400 pages of full-color, comprehensive instruction on the world's top drafting and architecture software. This 2015 edition features architectural, manufacturing, and landscape architecture examples. And like previous editions, the detailed guide introduces core concepts using interactive tutorials and open-ended projects, which can be completed in any order, thanks to downloadable data sets (an especially useful feature for students and professionals studying for Autodesk AutoCAD certification). Unlike man
AutoCAD 2012 and AutoCAD LT 2012 No Experience Required
Gladfelter, Donnie
2011-01-01
The perfect step-by-step introduction to Autodesk's powerful architectural design software With this essential guide, you'll learn how to plan, develop, document, and present a complete AutoCAD project by building a summer cabin from start to finish. You can follow each step sequentially or jump in at any point by downloading the drawing files from the book's companion web site. You'll also master all essential AutoCAD features, get a thorough grounding in the basics, learn the very latest industry standards and techniques, and quickly become productive with AutoCAD 2012.Features concise expla
AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility
Morris, Garrett M.; Huey, Ruth; Lindstrom, William; Sanner, Michel F.; Belew, Richard K.; Goodsell, David S.; Olson, Arthur J.
2009-01-01
We describe the testing and release of AutoDock4 and the accompanying graphical user interface AutoDockTools. AutoDock4 incorporates limited flexibility in the receptor. Several tests are reported here, including a redocking experiment with 188 diverse ligand-protein complexes and a cross-docking experiment using flexible sidechains in 87 HIV protease complexes. We also report its utility in analysis of covalently-bound ligands, using both a grid-based docking method and a modification of the...
Nonparametric LAD Cointegrating Regression
Toshio Honda
2011-01-01
We deal with nonparametric estimation in a nonlinear cointegration model whose regressor and dependent variable can be contemporaneously correlated. The asymptotic properties of the Nadaraya-Watson estimator are already examined in the literature. In this paper, we consider nonparametric least absolute deviation (LAD) regression and derive the asymptotic distributions of the local constant and local linear estimators by appealing to the local time approach.
Upper expectation parametric regression
Lin, Lu; Dong, Ping; Song, Yunquan; Zhu, Lixing
2014-01-01
Every observation may follow a distribution that is randomly selected in a class of distributions. It is called the distribution uncertainty. This is a fact acknowledged in some research fields such as financial risk measure. Thus, the classical expectation is not identifiable in general.In this paper, a distribution uncertainty is defined, and then an upper expectation regression is proposed, which can describe the relationship between extreme events and relevant covariates under the framewo...
Sublinear expectation linear regression
Lin, Lu; Shi, Yufeng; Wang, Xin; Yang, Shuzhen
2013-01-01
Nonlinear expectation, including sublinear expectation as its special case, is a new and original framework of probability theory and has potential applications in some scientific fields, especially in finance risk measure and management. Under the nonlinear expectation framework, however, the related statistical models and statistical inferences have not yet been well established. The goal of this paper is to construct the sublinear expectation regression and investigate its statistical infe...