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

Supporting Regularized Logistic Regression Privately and Efficiently

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Increasing concerns over data privacy make it more and more difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used machine learning model in various disciplines while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluation on several studies validated the privacy guarantees, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc

Molecular and phylogenetic characterization of honey bee viruses, Nosema microsporidia, protozoan parasites, and parasitic mites in China

China has the largest number of managed honey bee colonies, which produce the highest quantity of honey and royal jelly in the world; however, the presence of honey bee pathogens and parasites has never been rigorously identified in Chinese apiaries. We thus conducted a molecular survey of honey bee RNA viruses, Nosema microsporidia, protozoan parasites, and tracheal mites associated with nonnative Apis mellifera ligustica and native Apis cerana cerana colonies in China. We found the presence of black queen cell virus (BQCV), chronic bee paralysis virus (CBPV), deformed wing virus (DWV), Israeli acute paralysis virus (IAPV), and sacbrood virus (SBV), but not that of acute bee paralysis virus (ABPV) or Kashmir bee virus (KBV). DWV was the most prevalent in the tested samples. Phylogenies of Chinese viral isolates demonstrated that genetically heterogeneous populations of BQCV, CBPV, DWV, and A. cerana-infecting SBV, and relatively homogenous populations of IAPV and A. meliifera-infecting new strain of SBV with single origins, are spread in Chinese apiaries. Similar to previous observations in many countries, Nosema ceranae, but not Nosema apis, was prevalent in the tested samples. Crithidia mellificae, but not Apicystis bombi was found in five samples, including one A. c. cerana colony, demonstrating that C. mellificae is capable of infecting multiple honey bee species. Based on kinetoplast-encoded cytochrome b sequences, the C. mellificae isolate from A. c. cerana represents a novel haplotype with 19 nucleotide differences from the Chinese and Japanese isolates from A. m. ligustica. This suggests that A. c. cerana is the native host for this specific haplotype. The tracheal mite, Acarapis woodi, was detected in one A. m. ligustica colony. Our results demonstrate that honey bee RNA viruses, N. ceranae, C. mellificae, and tracheal mites are present in Chinese apiaries, and some might be originated from native Asian honey bees