Dual Channel Control with DC Fault Ride Through for MMC-based, Isolated DC/DC Converter

This study is sponsored by the Engineering and Physical Sciences Research Council (EPSRC) grant no EP/K006428/1, 2013.D. Jovcic and H. Zhang are with the School of Engineering, University of Aberdeen, AB24 3UE, U.K. ([email protected], [email protected]).Peer reviewedPostprin

Blind Ptychographic Phase Retrieval via Convergent Alternating Direction Method of Multipliers

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A ptychographyic reconstruction is normally formulated as a blind phase retrieval problem, where both the image (sample) and the probe (illumination) have to be recovered from phaseless measured data. In this article we address a nonlinear least squares model for the blind ptychography problem with constraints on the image and the probe by maximum likelihood estimation of the Poisson noise model. We formulate a variant model that incorporates the information of phaseless measurements of the probe to eliminate possible artifacts. Next, we propose a generalized alternating direction method of multipliers designed for the proposed nonconvex models with convergence guarantee under mild conditions, where their subproblems can be solved by fast element-wise operations. Numerically, the proposed algorithm outperforms state-of-the-art algorithms in both speed and image quality.Comment: 23 page

Non-convexity of the optimal exercise boundary for an American put option on a dividend-paying asset

In this thesis, we prove that the optimal exercise boundary of the American put option is not convex when the dividend rate of the underlying assetwhich follows a geometric Brownian motion, is slightly larger than the risk-free interest rate. We show that the non-convex region occurs very near the expiry time. Numerical evidence is also provided which suggests that the convexity of the optimal exercise boundary is restored when the dividend rate is sufficiently larger than the interest rate. In addition we provide the near-expiry and far-from-expiry behavior of the boundary. To complete the rigorous proofs, we also show that the optimal exercise boundary has $C^infty$ regularity

Partially Coherent Ptychography by Gradient Decomposition of the Probe

Coherent ptychographic imaging experiments often discard over 99.9 % of the flux from a light source to define the coherence of an illumination. Even when coherent flux is sufficient, the stability required during an exposure is another important limiting factor. Partial coherence analysis can considerably reduce these limitations. A partially coherent illumination can often be written as the superposition of a single coherent illumination convolved with a separable translational kernel. In this paper we propose the Gradient Decomposition of the Probe (GDP), a model that exploits translational kernel separability, coupling the variances of the kernel with the transverse coherence. We describe an efficient first-order splitting algorithm GDP-ADMM to solve the proposed nonlinear optimization problem. Numerical experiments demonstrate the effectiveness of the proposed method with Gaussian and binary kernel functions in fly-scan measurements. Remarkably, GDP-ADMM produces satisfactory results even when the ratio between kernel width and beam size is more than one, or when the distance between successive acquisitions is twice as large as the beam width.Comment: 11 pages, 9 figure

Community Participation In Cultural Heritage Tourism In Lijiang Old Town, China

Penglibatan komuniti dianggap sebagai salah satu strategi penting untuk merealisasikan pelancongan lestari di destinasi-destinasi warisan dan budaya. Namun begitu, di kawasan membangun, penglibatan komuniti adalah sangat kurang walaupun hal ini telah diberikan perhatian dalam bidang akademik semenjak tahun1980-an lagi. Community participation has been regarded as an indispensable strategy to realise the sustainable tourism in cultural heritage destinations. However, in developing regions, the community participation is very pessimistic in practice, although the importance has been stressed in academia since the 1980s

Machine Learning for Small Molecule Identification

Metabolites are small molecules involved in biological process of organisms. For example, ethylene serves as plants hormone to stimulate or regulate the opening of flowers, ripening of fruit and shedding of leaves. Metabolite identification is to figure out the molecular structure of the metabo-lite contained in some biological sample, which is considered as a major bottleneck for metabolo-mics. The backbone analytical technology for metabolite identification is tandem mass spectrometry. It consists two rounds of mass spectrometry: In the first round all the metabolites in a sample are measured and one particular metabolite being interested is selected and fragmented by a process of dissociation. In the second round, the fragments as well as their abundance are measured. The resulting tandem mass spectra contain the information on the structure and composition of the molecules. This thesis aims to solve the problem of identifying the molecular structures that produce the observed tandem mass spectra from some biological sample. The traditional methods are mostly based on matching the observed tandem mass spectra to the reference spectra in some database. However, these methods could fail if there are no reference spectra for the molecules in the underlying sample, which is not uncommon especially considering only 220,000 spectra representing 20,000 molecules are measured and annotated according to a recent study while the number of molecules recorded in a compound database PubChem is more than 60 million. To alleviate this problem, many recent works has been focusing on the approach so called in silico fragmentation where the fragmentations are first simulated in computer for the molecules in some molecular database. Then the simulated fragments are compared to the measured tandem mass spectra. The main contribution of this thesis is to open a novel direction to bridge the gap between the limited spectral database and the vast molecular database with the help of molecular fingerprints. Molecular fingerprints are a binary representation to encode the structures or properties of a molecule. Kernel based machine learning methods are used to predict the molecular fingerprints from tandem mass spectra. Then the predicted fingerprints are used to match the fingerprints of mole-cules in some molecular database to derive an identification. Multiple kernel learning are also proposed to combine different views of tandem mass spectra. Finally, a one-step approach based on input output kernel regression is also applied to solve this problem, which becomes the new state of the art as demonstrated in several benchmarks including the recent Critical Assessment of Small Molecule Identification (CASMI) 2016 challenge

A Fundamental Study into the Use of Different Ferrous Ores on Melt Characteristics of Sinter

Steelmakers are becoming more motivated to use iron ore resources with a wider range of grades and mineral types that were previously considered unsuitable or uneconomical for sintering. In this respect, specific issues which now require further investigation and understanding include the sintering of ores with a) overall higher gangue content, b) elements that cause problems in the steel manufacturing operations, and/or c) distinctive sintering performance compared with traditional hematite-rich iron ores. Laboratory-based investigation of the sintering performance and the behaviour of gangue impurities during sintering is an important step towards the successful utilisation of these resources in steelmaking. To explore the feasibility of small-scale sintering pot testing, a ‘millipot’ facility (diameter of 53 mm and height of 400 mm) was established and used to examine the sintering performance of iron ores and other non-traditional ferrous materials. The sintering performance of a millipot was examined across a range of operational conditions (coke rate and suction pressure) and compared with an industrial sinter strand operation. Tablet tests were also performed to assist in the design of the millipot experiments and identify conditions for achieving mineral composition similar to the industrial sinter. For the millipot experiments, the materials used need to be compacted to increase the bulk density, and a higher coke rate is required to compensate the high heat loss caused by wall effects. A higher suction pressure is also necessary to maintain an oxidising atmosphere in the sinter bed. As expected, it was not possible to completely eliminate the wall effect, which results in more primary hematite at edges of the sintered column. Heavier compacting at the periphery of the column can minimise the wall effect. The sintered material from the centre of column simulates industrial sinter reasonably well. As such, millipot provides a practical technique to evaluate the sintering process and material performance at laboratory scale, helping to bridge the gap between tablet sintering and large scale pot sintering, or full scale plant trials. The results of millipot testing can be used for designing larger scale experiments or commercial sintering trials..

A Review and Research Methodology of Chinese University EFL Students’ Perspectives on Anxiety in Native and Non-Native English Speaker Classes

The aim of this paper is to reveal how native and non-native speaker EFL (English as a foreign language) teachers influence students’ levels of Foreign Language Anxiety (FLA) in classrooms. Researchers in the area of second and foreign language acquisition have long been studying the role that anxiety plays among foreign language learners. Their findings are reported and analyzed in the first part of this paper. Then, research methodology is presented on two groups of students (180 in total) of whom 90 is in NS (Native Speaker) class and 90 in NNS (Non-Native Speaker) class taking English as a foreign language course for 4 hours a week at one university in China