Optimized Hierarchical Power Oscillations Control for Distributed Generation Under Unbalanced Conditions

Control structures have critical influences on converter-interfaced distributed generations (DG) under unbalanced conditions. Most of previous works focus on suppressing active power oscillations and ripples of DC bus voltage. In this paper, the relationship between amplitudes of the active power oscillations and the reactive power oscillations are firstly deduced and the hierarchical control of DG is proposed to reduce power oscillations. The hierarchical control consists of primary and secondary levels. Current references are generated in primary control level and the active power oscillations can be suppressed by a dual current controller. Secondary control reduces the active power and reactive power oscillations simultaneously by optimal model aiming for minimum amplitudes of oscillations. Simulation results show that the proposed secondary control with less injecting negative-sequence current than traditional control methods can effectively limit both active power and reactive power oscillations.Comment: Accepted by Applied Energ

Modeling Dependent Structure for Utterances in ASR Evaluation

The bootstrap resampling method has been popular for performing significance analysis on word error rate (WER) in automatic speech recognition (ASR) evaluation. To deal with dependent speech data, the blockwise bootstrap approach is also introduced. By dividing utterances into uncorrelated blocks, this approach resamples these blocks instead of original data. However, it is typically nontrivial to uncover the dependent structure among utterances and identify the blocks, which might lead to subjective conclusions in statistical testing. In this paper, we present graphical lasso based methods to explicitly model such dependency and estimate uncorrelated blocks of utterances in a rigorous way, after which blockwise bootstrap is applied on top of the inferred blocks. We show the resulting variance estimator of WER in ASR evaluation is statistically consistent under mild conditions. We also demonstrate the validity of proposed approach on LibriSpeech dataset

Complex electronic states in double layered ruthenates (Sr1-xCax)3Ru2O7

The magnetic ground state of (Sr$_{1-x}$Ca$_x$)$_3$Ru$_2$O$_7$ (0 $\leq x \leq$ 1) is complex, ranging from an itinerant metamagnetic state (0 $\leq x <$ 0.08), to an unusual heavy-mass, nearly ferromagnetic (FM) state (0.08 $< x <$ 0.4), and finally to an antiferromagnetic (AFM) state (0.4 $\leq x \leq$ 1). In this report we elucidate the electronic properties for these magnetic states, and show that the electronic and magnetic properties are strongly coupled in this system. The electronic ground state evolves from an AFM quasi-two-dimensional metal for $x =$ 1.0, to an Anderson localized state for $0.4 \leq x < 1.0$ (the AFM region). When the magnetic state undergoes a transition from the AFM to the nearly FM state, the electronic ground state switches to a weakly localized state induced by magnetic scattering for $0.25 \leq x < 0.4$, and then to a magnetic metallic state with the in-plane resistivity $\rho_{ab} \propto T^\alpha$ ($\alpha >$ 2) for $0.08 < x < 0.25$. The system eventually transforms into a Fermi liquid ground state when the magnetic ground state enters the itinerant metamagnetic state for $x < 0.08$. When $x$ approaches the critical composition ($x \sim$ 0.08), the Fermi liquid temperature is suppressed to zero Kelvin, and non-Fermi liquid behavior is observed. These results demonstrate the strong interplay between charge and spin degrees of freedom in the double layered ruthenates.Comment: 10 figures. To be published in Phys. Rev.

Joint Object and Part Segmentation using Deep Learned Potentials

Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision. In this paper, we propose a joint solution that tackles semantic object and part segmentation simultaneously, in which higher object-level context is provided to guide part segmentation, and more detailed part-level localization is utilized to refine object segmentation. Specifically, we first introduce the concept of semantic compositional parts (SCP) in which similar semantic parts are grouped and shared among different objects. A two-channel fully convolutional network (FCN) is then trained to provide the SCP and object potentials at each pixel. At the same time, a compact set of segments can also be obtained from the SCP predictions of the network. Given the potentials and the generated segments, in order to explore long-range context, we finally construct an efficient fully connected conditional random field (FCRF) to jointly predict the final object and part labels. Extensive evaluation on three different datasets shows that our approach can mutually enhance the performance of object and part segmentation, and outperforms the current state-of-the-art on both tasks

Integrated Design and Implementation of Embedded Control Systems with Scilab

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.Comment: 15 pages, 14 figures; Open Access at http://www.mdpi.org/sensors/papers/s8095501.pd