State-space ARIMA for supply-chain forecasting

ARIMA is seldom used in supply chains in practice. There are several reasons, not the least of which is the small sample size of available data, which restricts the usage of the model. Keeping in mind this restriction, we discuss in this paper a state-space ARIMA model with a single source of error and show how it can be efficiently used in the supply-chain context, especially in cases when only two seasonal cycles of data are available. We propose a new order selection algorithm for the model and compare its performance with the conventional ARIMA on real data. We show that the proposed model performs well in terms of both accuracy and computational time in comparison with other ARIMA implementations, which makes it efficient in the supply-chain context.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

GOS+MU:一种查询对象选择新方法

在分析单一MU(Most Uncertainty)采样缺陷的基础上,提出一种"全局最优搜寻"方法 GOS(Global Optimal Search),并结合MU共同完成查询选择。GOS+MU方法中,GOS着眼全局寻找目标,在应用环境能提供的训练样本数量有限、分类器受训不充分时,该方法选择的对象学习价值高,能快速推进分类器学习进程;MU则能够在GOS采样失效情形下,利用分类器当前训练成果,选择查询不确定性最强的样本补充训练集。通过对网络商品的用户评论进行分类仿真,并比较其他采样学习方法的效果,证明了GOS+MU方法在压缩学习成本、提高训练效率方面的有效性。     

枪管结构对固有频率的影响

为了研究枪管结构对枪管固有频率的影响,针对枪管尤其是狙击枪管设计中约束长度、枪管外形、膛口装置以及膛线等不同结构,建立了相应的三维模型。采用以六面体为主的网格对枪管进行了网格划分,采用有限元方法对枪管进行了模态分析。计算获得了不同结构枪管的固有频率; 通过比较,得到了不同枪管结构对固有频率的影响。分析结果表明:枪管尾部螺纹长度越长,枪口振动幅度越低; 相同质量枪管,锥形外形枪管刚度最好; 加装膛口装置对枪管刚度和振动特性有不利影响。     

Polyaniline-based networks combined with Fe3O4 hollow spheres and carbon balls for excellent electromagnetic wave absorption

Polyaniline (PANI)-based networks combined with Fe₃O₄ hollow spheres and carbon balls (FCP) for improved electromagnetic wave (EMW) absorption were investigated using an easy-to-industrialize solvothermal and physical method. Hollow structure Fe₃O₄ spheres with a lower density than that of the common solid sphere were prepared. As a thin and light magnetic material, Fe₃O₄ hollow spheres generate magnetic loss, carbon balls and PANI networks generate dielectric loss. The magnetic and conductive parts play appropriate roles in achieving complementarity in the EMW absorption. The relatively high specific surface area introduced by PANI networks promotes interfacial polarization and further supports dielectric loss. In conclusion, the above reasons provide multiple attenuation mechanisms. Samples FCP1 (?65.109 dB, at 12.800 GHz, 1.966 mm, from 5.6 to 18.0 GHz) and FCP2 (?61.033 dB, at 8.480 GHz, 3.328 mm, from 4.3 to 18.0 GHz) demonstrated a wide bandwidth, a small thickness, a minimum reflection loss (R_L), and a low loading ratio (25%) in paraffin-based composites. Specifically, their loading ration of 25% is much lower than the loading ratio of conventional materials (usually 50% and above). In addition, the bandwidth is excessively wide, above 12 GHz, possessing good absorption performance in continuous intervals with different thicknesses. Such excellent characteristics have rarely been reported in literature.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Microstructure,tribological behavior and magnetic properties of Fe−Ni−TiO2 composite coatings synthesized via pulse frequency variation

The Fe−Ni−TiO₂ nanocomposite coatings were electrodeposited by pulse frequency variation. The results showed that the nanocomposite with a very dense coating surface and a nanocrystalline structure was produced at higher frequencies. By increasing the pulse frequency from 10 to 500 Hz, the iron and TiO₂ nanoparticles contentswere increased in expense of nickel content. XRD patterns showed that by increasing the frequency to 500 Hz, an enhancement ofBCC phase was observed and the grain size of deposits was reduced to 35 nm. The microhardness and the surface roughness were increased to 647 HV and 125 nm at 500 Hz due to the grain size reduction and higher incorporation of TiO₂ nanoparticles into the Fe−Ni matrix (5.13 wt.%). Moreover, the friction coefficient and wear rate values were decreased by increasing the pulse frequency;while the saturation magnetization and coercivity values of the composite deposits were increased.     

ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis

Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize frequency band location including a fault transient out of a full band spectrum, and thus fault diagnosis can suppress noise influence from other frequency components. Impulsiveness and cyclostationarity have been recently recognized as two distinctive signatures of a transient. Thus, many studies have focused on developing quantification metrics of the two signatures and using them as indicators to guide FBS. However, most previous studies almost ignore another aspect of FBS, i.e. health reference, which significantly affect FBS performance. To address this issue, this paper investigates importance of a health reference and recognize it as the third critical aspect in FBS. With help of the health reference, the frequency band where the fault transient exists could be located. A novel approach based on classification is proposed to integrate all three aspects (impulsiveness, cyclostationarity, and health reference) for FBS. Classification accuracy is developed as a novel indicator to select the most sensitive frequency band for rotating machinery fault diagnosis. The proposed method (coined by accugram) has been validated on benchmark and experiment datasets. Comparison results show its effectiveness and robustness over conventional envelope analysis, the kurtogram, and the infogram.     

A Stimulation Method to Assess the Contractile Status of the Lumbar Extensors in a Seated Posture

The purpose of present study was to develop and evaluate methods to assess stimulation responses of the lumbar extensors, as part of a longer‐term goal of detecting fatigue during prolonged sitting. Three stimulation frequencies (2, 5, and 8 Hz) were tested in separate stages, which include 3 stimulation trains and 4 sampling blocks. Repeated measures analyses of variance were used to determine whether any significant differences in mean stimulation responses occurred with respect to stimulation frequency, sampling block, and stimulation train. Reliability of measured stimulation responses was assessed within and between sampling blocks using intraclass correlation coefficients. Stimulation frequencies significantly affected the stimulation responses and time‐to‐potentiation differed between the 3 stimulation frequencies; it was highest for 2 Hz stimulation. All 3 stimulation frequencies resulted in excellent reliability within and between sampling blocks. Use of the current protocol at 2 Hz is recommended as appropriate to measure the lumbar extensors status during prolonged sitting.     

PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees

The need for feature selection and dimension reduction is felt as a fundamental step in security assessment of large power systems in which the number of features representing the state of power grids dramatically increases. These large amounts of attributes are not proper to be used for computational intelligence (CI) techniques as inputs, because it may lead to a time consuming procedure with insufficient results and they are not suitable for on-line purposes and updates.This paper proposes a combined method for an online voltage security assessment in which the dimension of the token data from phasor measurement units (PMUs) is reduced by principal component analysis (PCA). Then, the features with different stability indices are put into several categories and feature selection is done by correlation analysis in each category. These selected features are then given to decision trees (DTs) for classification and security assessment of power systems.The method is applied to 39-bus test system and a part of Iran power grid. It is seen from the results that the DTs with reduced data have simpler splitting rules, better performance in saving time, reasonable DT error and they are more suitable for constant updates.