Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

Annular‐ring slot antenna designs with circular polarization radiation

The design of a microstrip‐fed annular‐ring slot antenna (ARSA) with circular polarization (CP) radiation is initially studied. To obtain CP radiation with broad 3‐dB axial ratio (AR) bandwidth that can cover the WiMAX 2.3 GHz (2305–2320 MHz, 2345–2360 MHz) and WLAN 2.4 GHz (2400–2480 MHz) bands, a novel technique of extending an inverted L‐shaped slot from the bottom section of the annular‐ring is proposed. To suppress the harmonic modes induced by the CP ARSA, the technique of integrating a defected ground structure into the annular‐ring slot is further introduced. From the measured results, 10‐dB impedance bandwidth and 3‐dB AR bandwidth of 44.86 and 9.68% were achieved by the proposed harmonic suppressed CP ARSA. Furthermore, average gain and radiation efficiency of ～4.7 dBic and 71%, respectively, were also exhibited across the bands of interest. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:337–345, 2015.     

基于矢量平均的信道估计算法

提出一种适用于DS-CDMA无线通信系统的低计算量而性能良好的信道估计算法。在DS-CDMA系统中，当接收信号经过解扩或多用户检测等时域预处理后，可以认为干扰大大减弱、期望信号在处理后的信号中占主要地位。这样，用预处理后信号相关阵的最大特征值对应的特征矢量可以很好地近似期望信号的信道矢量。但是，直接特征分解需要很大的计算量，特征跟踪计算量较低，但瞬态性能较差。本文提出一种基于相关矩阵列矢量平均的信道估计算法，该算法不需要特征分解或跟踪。仿真结果表明：新算法在降低计算量的情况下可以获得同直接特征分解方法几乎相同的性能。     

XAZ340-4GF反洗压滤机的研制与应用

介绍了XAZ340-4GF反洗压滤机的研制过程,介绍了该机型的结构\原理\工艺系统.并简要介绍了其工业应用情况。     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

激电法找油的原理及应用

激电法是非地震物探手段中的一种，由于油气在向上渗透的过程中会与地层发生一系列的生物。化学反应而形成次生黄铁矿，激电法正是通过发现油气藏上方形成的次生黄铁矿晕来寻找油气的一种间接找油方法。通过详细介绍激电法寻找油气的基本原理。仪器设备等，从实践角度论述了激电法在油田勘探开发中的应用范围及其特点，最后通过兴例说明了其良好的应用效果。     

InP基应变补偿结构偏振不灵敏半导体光放大器制作的研究

为了制备偏振不灵敏的半导体光放大器(SOA)，将有源区设计为由4个压应变、3个张应变阱层及晶格匹配的垒层InGaAsP交替组合而成的应变补偿结构。器件做成带有倾角的扇形脊形波导结构，避免了常规制作SOA的复杂工艺。对样品3在80～125mA电流范围内，获得了偏振灵敏度≤0．6dB．最小可达0．1dB；较大的电流范围内FWHM值为40nm。     

红外目标精跟踪方法的研究

本文提出了一种直接把红外前视传感器的输出作为测量值来跟踪红外目标的扩展型卡尔曼滤波跟踪算法。在滤波处理时,设置可变的测量矩阵,其目的在于提高运算速度和抑制噪声干扰。通过具体的实例,对所提跟踪算法的特点和有效性进行了细致的分析。