Function Decomposition Method Research Articles

Dynamic Correlation Analysis of Construction Industry Development Level and Science and Technology Innovation

This paper analyzes the relationship between the technological innovation of the construction industry and the development level of the construction industry from the perspective of input and output in the construction industry. Using the time series data from 1995-2017, a vector autoregressive (VAR) model was established. The article uses co-integration analysis, Granger causality test, impulse response function and variance decomposition method to study the index variables. The long-term equilibrium relationship and short-term fluctuation effects between China’s construction industry development, construction industry science and technology innovation investment and output are analyzed. The results show: there are long-term equilibrium relationships and one-way causal relationships between the three variables, and there is time lag. The output of science and technology innovation in the construction industry is positively responded to itself, the development level of the construction industry and the investment in science and technology innovation in the construction industry. Among them, it is most affected by the fluctuation of investment in science and technology innovation. Compared with the development level of the construction industry, the contribution of scientific and technological innovation to the output of scientific and technological innovation is even greater. Finally, relevant policy recommendations for the development of the construction industry and technological innovation in the construction industry are given.

A convex-nonconvex variational method for the additive decomposition of functions on surfaces

We present a convex-nonconvex variational approach for the additive decomposition of noisy scalar fields defined over triangulated surfaces into piecewise constant and smooth components. The energy functional to be minimized is defined by the weighted sum of three terms, namely an fidelity term for the noise component, a Tikhonov regularization term for the smooth component and a total variation (TV)-like non-convex term for the piecewise constant component. The last term is parametrized such that the free scalar parameter allows to tune its degree of non-convexity and, hence, to separate the piecewise constant component more effectively than by using a classical convex TV regularizer without renouncing to convexity of the total energy functional. A method is also presented for selecting the two regularization parameters. The unique solution of the proposed variational model is determined by means of an efficient ADMM-based minimization algorithm. Numerical experiments show a nearly perfect separation of the different components.

Timing Circuit Design Based on Sequential Logic and Micro-processing Technology

According to the need of equipment testing, the paper presented the overall scheme of timing circuit and the wiring diagram of hardware circuit, and also designed the indicator circuit, the timing software and the band switch circuit. Then modular design concept and function decomposition method were adopted, and the time sequence step-by-step technology and safety isolation technology were used to solve the difficulty and credibility of acquiring multi-functional components, multi-system modules and complex multi-channel correlated signal interference problem. Finally, the off-line debugging was carried out. The results show that the technology can test the functions and performance indexes of the plug-in board comprehensively and completely, realize the functions of depth setting system debugging, extension testing and fault precise location, and shorten the maintenance and detection time.

Trade liberalization and haze pollution: Evidence from China

Abstract This paper investigates the impacts of trade liberalization on haze pollution using the panel data for 279 Chinese prefecture-level cities during 2007–2016. The relationship of trade liberalization and haze pollution in China was firstly analyzed by using the impulse response function and forecast-error variance decomposition method based on a bivariate vector autoregression model. The results show that trade liberalization is negatively correlated with haze pollution, and the contribution of trade liberalization to the variance of haze pollution exceeds 70% over time. The impact of trade liberalization on haze pollution is further examined applying the two-way fixed effect methods and spatial lag models, concluding that the liberalization of trade has significantly reduced haze pollution. Through mediation effect method, we have found that the haze reduction effect of trade liberalization lies in that the positive influence of technology effect on reducing haze pollution has exceeded the negative influence of scale effect and composition effect on increasing haze pollution. Therefore, in general, trade liberalization has remarkably mitigated haze pollution. The conclusions of this paper will provide a reference for the haze pollution reduction policies and the coordinated development of economic growth and environmental quality.

A global empirical orthogonal function model of plasmaspheric electron content

Based on the method for establishing a global plasmaspheric model using observations from COSMIC and MetOp-A orbit determination GNSS receivers, Chen et al. (2017) obtained a global plasmaspheric total electron content product with a spatial resolution of 2.5° × 5° and a time resolution of 4 h. In this paper, we use those global plasmaspheric electron content product in 2008, 2010, 2011, 2012, 2014 for 1446 days to establish a global plasmaspheric empirical model based on empirical orthogonal function (EOF). The model can well characterize the spatiotemporal variation of plasmaspheric electron content (PEC) and the influence of solar radiation on it. Only the first four orders of EOF sequences can characterize the 98.43% features of the original PEC dataset. The principal component coefficient Pk is decomposed twice during modeling, and the combination of trigonometric function and linear function is used to model Pk to characterize the solar cycle, annual cycle, semi-annual cycle and quarter-cycle variation. We compare the PEC model values with the actual observation data, the results show that the empirical PEC model values are highly correlated with the actual observations. The correlation between the two is above 0.96, and the RMS maximum of the difference between the PEC model values and the observed values are 0.70 TECU, and the average of the difference between the PEC model values and the observed values are −0.18 TECU, respectively. In addition, we validate the reliability of the global plasmaspheric model established by two empirical orthogonal function decomposition method using actual observation data, according to the global distribution of the differences between the PEC model values and the observed values in low solar activity and high solar activity, it can be seen that under low solar activity and high solar activity conditions, the model has good adaptability.

A Business Process Framework and Operations Map for Maritime Autonomous and Unmanned Shipping: MAUSOM

Maritime autonomous and unmanned shipping have considerable potential for cost-effective and safe cargo or passenger transport and other maritime operations. Such a manner of shipping will introduce operations chains with new roles and responsibilities. Widescale adoption requires an agreed upon overarching business process framework and operations map. Therefore, this paper introduces MAUSOM: the Maritime Autonomous and Unmanned Shipping Operations Map. Within the maritime industry and research community MAUSOM can be used as a shared blueprint for (re-)designing the operations processes and for defining the supporting functional capabilities. Furthermore, it structures the task allocation process to identify those tasks that can and those that (currently) cannot be allocated to software modules. Furthermore, it enables the definition of the data models needed for the overall system design. The MAUSOM methodology is based on the similar and successful enhanced Telecom Operations Map (eTOM) framework approach from the telecommunication sector [11]. MAUSOM uses Hierarchical Task Analysis (HTA), which has a long tradition as human factors’ functional decomposition method for engineering maritime operations. This paper describes MAUSOM, the benefits of its standardization and adoption for various stakeholders in the maritime shipping operations chain and addresses its development and deployment governance aspects.

A Spatiotemporal Estimation Framework for Real-World LIDAR Wind Speed Measurements

Despite significant advances in the remote sensing of fluid flows, light detection and ranging (LIDAR) measurement equipment still presents the problems of having only radial (line-of-sight) wind speed measurements (Cyclops' dilemma). Substantial expanses of unmeasured flow still remain and range weighting errors have a considerable influence on LIDAR measurements. Clearly, more information needs to be extracted from LIDAR data. With this motivation in mind, this brief shows that it is possible to estimate the wind velocity, wind direction, and absolute pressure over the entire spatial region of interest. A key challenge is that most established estimation techniques cater for systems that are finite-dimensional and described by ordinary differential equations (ODEs). By contrast, many fluid flows are governed by the Navier-Stokes equations, which are partial differential-algebraic equations (PDAEs). We show how a basis function decomposition method in conjunction with a pressure Poisson equation (PPE) formulation yields a spatially continuous, strangeness-free, reduced-order dynamic model for which a modified DAE form of the unscented Kalman filter (UKF) algorithm is used to estimate unmeasured velocities and pressure using sparse measurements from wind turbine-mounted LIDAR instruments. The approach is validated for both synthetic data generated from large eddy simulations of the atmospheric boundary layer and real-world LIDAR measurement data. Results show that a reconstruction of the flow field is achievable, thus presenting a validated estimation framework for potential applications including wind gust prediction systems and the preview control of wind turbines.

A study of the ionospheric disturbances associated with strong earthquakes using the empirical orthogonal function analysis

In this study, an ionospheric logTEC model has been constructed using an empirical orthogonal function (EOF) decomposition method. The main orders (1–9 orders) of this EOF model represent the ionospheric background, while the rest high orders represent ionospheric TEC perturbations. Based on this model, logTEC data during 16 Ms ≥ 8.0 earthquakes from 2000 to 2012 have been analyzed. We found that ionospheric disturbances occurred in 10 earthquakes. Ionospheric abnormities were clearly observed 5 days before the earthquakes, but ionospheric disturbances can also be seen 1 day before, and 1 day and 2 days after the earthquakes. For the TEC data, the possibility of positive (enhanced TEC) and negative (decreased TEC) abnormities is almost the same. Furthermore, by using the simulation results of ionospheric electric field and SAMI2 model, we show that an abnormal westward electric field can lead to electron density enhancements equatorward and decrease polarward of the epicenters, and vice versa for an eastward abnormal electric field.

Extreme wave climate variability in South China Sea

Extreme wave climate variability in the South China Sea (SCS) was investigated using significant wave height (SWH) data simulated by the third generation wave model WAVEWATCH-III (WW-III) for the period 1976–2014. The wind forcing data was using the objective reanalysis wind dataset from the weather research and forecasting (WRF) model. The simulated SWH was well validated by observation data from satellite altimeter and in-situ buoys. A generalized extreme value (GEV) model was applied to analyze the extreme wave climate variability. Monthly significant wave height maxima is used to characterize the seasonal variability. The spatial distributions of positional and scale parameters are achieved. The positional parameter values reach the maximum in winter, while the scale parameter values are greater in summer and autumn due to the impact of typhoon. The regression analysis of harmonic functions was applied to give the annual cycle. Interannual climatology of extreme wave climate from Empirical Orthogonal Function (EOF) decomposition method and spectrum analysis method revealed a dominant 12 months period and a 22 months period, respectively. Results show that El Nino may significantly affect the extreme wave climate variability in the SCS.

Global sensitivity analysis and multi-objective optimization design of temperature field of sinter cooler based on energy value

Sinter cooler, as sinter cooling process equipment, is used to cool the hot sinter to be lower than specified temperature. While the hot gas produced in sinter cooling process is usually recovered and utilized to reduce the energy consumption in recent years. In present study, a global sensitivity-based optimization design method synthesizing both the performances of sinter cooling and energy conservation of sinter cooler was proposed. Firstly, based on the Latin hypercube sampling technique and radial basis neural network approach, an accurate metamodel of the sinter cooler was established. Secondly, to select the significant operating parameters, a global sensitivity analysis was performed to evaluate exactly the sensibility of the indicator parameters with respect to operating parameters. In the analysis, a function decomposition method was firstly introduced into sinter cooler analysis to obtain the global sensitivity indices of operating parameters. Finally, based on the results of global sensitivity analysis, a multi-objective optimization was performed to achieve the optimal indicator parameters and obtain corresponding operating conditions using nondominated sorting genetic algorithm II (NSGA-II). At the end, a Pareto frontier as a group of non-dominated optimal solutions was suggested for engineers to be selected according to actual situation.

Study on the relationship between per capita tourism expenditure and disposable income of urban residents – Empirical analysis based on VAR model

The article constructs the VAR model, and empirically studies the interaction between per capita travel expenditure and disposable income of Chinese urban residents through impulse response function and variance decomposition method. The conclusion of the study shows that there is a long-term dynamic cointegration relationship between tourism expenditures and disposable income of urban residents in China, but the promotion between them is not enough.

Magnetic anomaly detection based on stochastic resonance

Orthonormal basis function (OBF) decomposition method and minimum entropy (ME) detector are two typical methods of magnetic anomaly detection. The OBF detector works effectively only when the assumptions of the target signal and noise are appropriate, and the ME detector is limited by low signal-to-noise ratio (SNR). In order to improve magnetic anomaly detection performance in the case of low SNR and no prior information of the target signal, we proposed a novel detector by using stochastic resonance (SR) method and named it SR detector in the paper. The SR detector consists of a bistable SR system and a corresponding receiver. Firstly, the noise is used to enhance the magnetic anomaly signal with the help of SR system, instead of being suppressed in a traditional method; then the anomaly signal can be detected more effectively by the receiver. Experimental results show that the SR detector did work well, its detection probability approximated to 70% even if the input SNR was −3 dB, and was about 100% if the input SNR was 0dB, when the false alarm rate (FAR) was 1.5%. Furthermore, the SR detector provided higher detection probability than the ME detector under the same basis. In a word, due to the good detection performance and simple implementation, the SR detector would be more attractive in practice.

Dynamic characteristics of a large‐diameter pile in saturated soil and its application

SummaryThis study theoretically investigates the dynamic response of an end‐bearing pile embedded in saturated soil considering the transverse inertial effect of the pile. The saturated soil surrounding the pile is described by Biot poroelastic theory, and the pile is represented by a Rayleigh‐Love rod because both the vertical and radial displacements at the soil‐pile interface are considered. The potential function decomposition method and variable separation method are introduced to solve the governing equations of the soil, in which the vertical and radial displacement components are coupled. The governing equation of the pile is solved using the continuity conditions at the pile‐soil interface. Next, the velocity admittance in the frequency domain and the velocity response in the time domain at the pile top are presented based on the Laplace transform and inverse Fourier transform, respectively. Subsequently, the reduced solution is compared with a 1‐dimensional model solution to verify the validity, and the influences of the slenderness ratio of the pile on the transverse inertial effect of the pile are analyzed. Moreover, Poisson ratio, the slenderness ratio of the pile, and the pile‐soil modulus ratio are studied. Finally, the theoretical and measured curves in the engineering project are compared, and the results demonstrate the good application prospects of the solution presented in this article.

Decomposing the links between oil price shocks and macroeconomic indicators: Evidence from SAARC region

This study examines the impact of oil price shocks on key macroeconomic variables (i.e., real GDP, interest rate, inflation and exchange rate) for five SAARC countries (i.e., India, Pakistan, Bangladesh, Sri Lanka and Bhutan). For this purpose, we adopt contemporary macroeconomic policy modeling tool called impulse response function (IRF) and forecast error variance decomposition method (FEVDM) in the structural vector autorepression (SVAR) setting using time series data over the extended period from 1982 to 2014. In addition, Johansen (1991) cointegration method is applied for long-run relationship. The results of cointegration test confirms the long-run equilibrium relationship between all the underlying variables. However, the empirical findings of IRF explained significant variation among all underlying macroeconomic variables in response to exogenous oil price shocks at different time horizons. It means the macroeconomic factors are sensitive to even small oil price shocks and possess various socio-economic implications in the region. The results of FEVDM evidence that each country in a study group responds differently to oil price shocks, it corresponds their independent policies, macroeconomic fundamentals, sector constructions and heterogeneity across the countries. The findings help governments to reform public policies in the region by controlling macroeconomic fluctuations due to oil price shocks.

Reexamining the determinants of foreign direct investment in China

This study examines significant determinants of foreign direct investment (FDI) inflows in China using bounds test approach for the period of 1980–2015. It shows that the main determinants of FDI include labour cost, size of market (gross domestic product, GDP), trade openness, economic policy uncertainty, and real exchange rate. The system of the Vector Auto Regressive (VAR) Model with Impulse Response Function (IRF) and Variance Decomposition Method (VDM) is used to empirically demonstrate the relationship between FDI and its main determinants in China. The study also examines the causality of the relationship, drawing on Granger Causality test and the Toda-Yamamoto-Dolado Lutkephol (TYDL) approach. It is revealed that FDI and its determinants have bidirectional causal relationship in the long-run and also a significant relationship in the short-run. The study finds that the extra volume of inward FDI can be attracted when emerging market economies try to open for external trade. Furthermore, it suggests that the GDP growth is an important determinant of FDI inflow. Such a result implies that policy makers need to establish a more effective, liberal and transparent FDI policy framework, which can help the FDI-based policies lead to stimulating economic growth.

Thermocline Fluctuations in the Equatorial Pacific Related to the Two Types of El Niño Events

The interannual fluctuations of the equatorial thermocline are usually associated with El Niño activity, but the linkage between the thermocline modes and El Niño is still under debate. In the present study, a mode function decomposition method is applied to the equatorial Pacific thermocline, and the results show that the first two dominant modes (M1 and M2) identify two distinct characteristics of the equatorial Pacific thermocline. The M1 reflects a basinwide zonally tilted thermocline related to the eastern Pacific (EP) El Niño, with shoaling (deepening) in the western (eastern) equatorial Pacific. The M2 represents the central Pacific (CP) El Niño, characterized by a V-shaped equatorial Pacific thermocline (i.e., deep in the central equatorial Pacific and shallow on both the western and eastern boundaries). Furthermore, both modes are stable and significant on the interannual time scale, and manifest as the major feature of the thermocline fluctuations associated with the two types of El Niño events. As good proxies of EP and CP El Niño events, thermocline-based indices clearly reveal the inherent characteristics of subsurface ocean responses during the evolution of El Niño events, which are characterized by the remarkable zonal eastward propagation of equatorial subsurface ocean temperature anomalies, particularly during the CP El Niño. Further analysis of the mixed layer heat budget suggests that the air–sea interactions determine the establishment and development stages of the CP El Niño, while the thermocline feedback is vital for its further development. These results highlight the key influence of equatorial Pacific thermocline fluctuations in conjunction with the air–sea interactions, on the CP El Niño.

Decomposing Multifractal Crossovers.

Physiological processes—such as, the brain's resting-state electrical activity or hemodynamic fluctuations—exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for the topology of multifractal metrics free of the masking effect of the underlying random noise.

The relationship between international crude oil prices and China\u2019s refined oil prices based on a structural VAR model

With the frequent fluctuations of international crude oil prices and China’s increasing dependence on foreign oil in recent years, the volatility of international oil prices has significantly influenced China domestic refined oil price. This paper aims to investigate the transmission and feedback mechanism between international crude oil prices and China’s refined oil prices for the time span from January 2011 to November 2015 by using the Granger causality test, vector autoregression model, impulse response function and variance decomposition methods. It is demonstrated that variation of international crude oil prices can cause China domestic refined oil price to change with a weak feedback effect. Moreover, international crude oil prices and China domestic refined oil prices are affected by their lag terms in positive and negative directions in different degrees. Besides, an international crude oil price shock has a significant positive impact on domestic refined oil prices while the impulse response of the international crude oil price variable to the domestic refined oil price shock is negatively insignificant. Furthermore, international crude oil prices and domestic refined oil prices have strong historical inheritance. According to the variance decomposition analysis, the international crude oil price is significantly affected by its own disturbance influence, and a domestic refined oil price shock has a slight impact on international crude oil price changes. The domestic refined oil price variance is mainly caused by international crude oil price disturbance, while the domestic refined oil price is slightly affected by its own disturbance. Generally, domestic refined oil prices do not immediately respond to an international crude oil price change, that is, there is a time lag.

An automated functional decomposition method based on morphological changes of material flows

ABSTRACTConceptual design has been paid increasing attention by academia and industry. However, there is no consensus of the concept of ‘function’ in the domain of conceptual design, making automated functional decomposition a difficult problem. The goal of this study is to develop an automated functional decomposition method based on the formal representation to model the morphological changes of material flows. Hierarchical material structure representation and a hierarchical shape graph are used to abstract the morphological properties of a material. Based on the semantics contained in the input and output material flows, together with decomposition principles, an overall function is broken into several sub-functions. Moreover, a sequence-planning algorithm of sub-functions is provided to facilitate achieving all of the morphological changes of a material flow. Finally, the proposed method is implemented, and some analyses are provided.

Adaptive Fourier decomposition‐based Dirac type time‐frequency distribution

The Dirac‐type time‐frequency distribution (TFD), regarded as ideal TFD, has long been desired. It, until the present time, cannot be implemented, due to the fact that there has been no appropriate representation of signals leading to such TFD. Instead, people have been developing other types of TFD, including the Wigner and the windowed Fourier transform types. This paper promotes a practical passage leading to a Dirac‐type TFD. Based on the proposed function decomposition method, viz., adaptive Fourier decomposition, we establish a rigorous and practical Dirac‐type TFD theory. We do follow the route of analytic signal representation of signals founded and developed by Garbo, Ville, Cohen, Boashash, Picinbono, and others. The difference, however, is that our treatment is theoretically throughout and rigorous. To well illustrate the new theory and the related TFD, we include several examples and experiments of which some are in comparison with the most commonly used TFDs. Copyright © 2016 John Wiley & Sons, Ltd.