Wasserstein Distance Guided Representation Learning for Domain Adaptation

Domain adaptation aims at generalizing a high-performance learner on a target domain via utilizing the knowledge distilled from a source domain which has a different but related data distribution. One solution to domain adaptation is to learn domain invariant feature representations while the learned representations should also be discriminative in prediction. To learn such representations, domain adaptation frameworks usually include a domain invariant representation learning approach to measure and reduce the domain discrepancy, as well as a discriminator for classification. Inspired by Wasserstein GAN, in this paper we propose a novel approach to learn domain invariant feature representations, namely Wasserstein Distance Guided Representation Learning (WDGRL). WDGRL utilizes a neural network, denoted by the domain critic, to estimate empirical Wasserstein distance between the source and target samples and optimizes the feature extractor network to minimize the estimated Wasserstein distance in an adversarial manner. The theoretical advantages of Wasserstein distance for domain adaptation lie in its gradient property and promising generalization bound. Empirical studies on common sentiment and image classification adaptation datasets demonstrate that our proposed WDGRL outperforms the state-of-the-art domain invariant representation learning approaches.Comment: The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018

Developing atom probe tomography for unique nanoscale insights into biomaterials

Bone provides structure and support for vertebrates, and it is the largest ion exchanger in the body to maintain homeostasis. Bone is a complex and heterogeneous composite material mainly composed of inorganic phases (mineral), organic phases (collagen, non-collagenous proteins), and water. Understanding the spatial structure and chemical composition of bone across different length scales is of great significance for elucidating its biomineralization mechanism, mechanical support, bone pathological treatment, and bone scaffold development. However, the simultaneous characterization of structure and chemical information of bone at the nanoscale presents many limitations, especially the exploration of 3D spatial structure and the mapping of low atomic mass elements. Among the many synthetic bone substitutes, bioactive glasses (BG) are an attractive candidate with applications in critical bone damage repair, as they stimulate biological responses that favor bone formation and angiogenesis. However, previously it has been difficult to develop an amorphous BG that combines a 3D porous structure with a strong biological activity because conventional BG easily crystallizes during processing. The crystallization of bioactive glass limits the dissolution rate of the material and therefore slows down the surface reactivity, leading to a decrease in scaffold bioactivity and bone regeneration capabilities. In recent years, a new amorphous 3D strontium-containing BG (pSrBG) scaffold was developed by adding strontium to increase the bioactivity of BG. Prior characterization of this material showed a scaffold with a near-perfect bone contact without fibrous tissue coverage, and that it supports nearly exclusively lamellar bone repair, similar to normal and functional bone. Besides, strontium was detected in new form bone and plasma after 21 days of transplantation in vivo, indicating that strontium successfully diffused as the material dissolved. However, due to the detection limits of conventional characterization techniques, it was not possible to specify the precise locality of released ions, and hence, it is not clear whether the locally achievable strontium concentration at the interface exceeds the medically acceptable range. Furthermore, the mechanism of Sr uptake into the bone and bone repair remains inconclusive. Atom probe tomography (APT) is a 3D microscopy characterization technique with a unique combination of high spatial and chemical resolution, which can be used to characterize this new type of biomaterial, animal bone, and the interface between material and bone. The work in this thesis presents the enabling preliminary development of APT techniques prior to this interface analysis. The synthetic bone material and porcine trabecular bone were investigated and characterised using APT. The challenges and corresponding countermeasures of biomaterials for APT sample preparation and experiments are outlined. The influence of various experimental parameters such as temperature, detection rate, laser pulse energy, and pulse frequency on the data quality by the LEAP-5000XR is explored and discussed. To this end, optimal operating conditions of APT were investigated and selected for two strontium-containing bioactive glass particles, the pSrBG scaffold, and porcine trabecular bone. The structure, including the spatial distribution of collagen and mineral phases, and their chemical composition were analyzed at the atomic level within the porcine trabecular bone. The challenges and limitations of APT in reconstruction analysis and quantitative chemical composition measurements of biomaterials are addressed. This study demonstrates that APT has the unique capacity to identify and characterize significant compositional variations in nanoscale volumes within individual bone phases that may provide new insights into the further development and demonstration of the potential of APT in exploring the spatial structure and chemical composition of bones. It also provides the basis for advancing knowledge in APT research at the interface of pSrBG and bone

Effects of elevated ozone on winter wheat and potential genetic and physiological mechanisms

Wheat is an ozone-sensitive crop with substantial global yield loss. It is necessary to make assessments of ozone impacts and to investigate the tolerance mechanisms and genetic factors conferring ozone tolerance in wheat. Contrasting wheat cultivars had been pre-selected from a larger wheat population with known ozone tolerance and exposed to season-long ozone fumigation in open-top chambers. Season-long ozone fumigation was conducted at an average ozone concentration of 70 ppb with three additional acute ozone episodes of around 150 ppb. This thesis is structured into three major parts: (1) Based on the large variations of ozone responses in wheat, physiological traits contributing to yield losses or yield stability were identified under ozone stress in eighteen contrasting genotypes for modelling parameterization, that is, foliar chlorophyll content represented by normalized difference vegetation index and net CO2 assimilation rate of young leaves during grain filling. LINTULCC2 crop model was further parametrized for two selected tolerant or sensitive varieties, respectively, with an ozone response routine. Parameters representing the distinct physiological responses of contrasting genotypes were specified to improve the accuracy of modelling simulation. (2) Carbon (C) and nitrogen (N) allocation were analyzed in straw and grains under ozone stress. Elevated ozone exposure reduced the N absorption from soil and allocation from vegetative to reproductive organs, manifested as significantly reduced indicators of N use efficiency (NUE) with the exception of N utilization efficiency (NUtE). In addition, the relationship between harvest index (HI) and nitrogen harvest index (NHI) was changed by ozone stress, and the reduced regression slope between them indicated that ozone exposure significantly affected the relationship of N and biomass allocation into wheat grain. (3) According to genetic backgrounds at ozone tolerant loci, tolerant and sensitive haplotypes represented by two genotypes, respectively, were used for gene expression, physiological and biochemical analyses. Tolerant and sensitive haplotypes showed consistently contrasting responses to ozone in terms of net photosynthetic rate, lipid peroxidation, apoplastic ascorbate, ascorbate peroxidase and peroxidase activity. Among candidate genes located within an ozone tolerant locus on chromosome 5A 592.04 - 593.33 Mb, the gene TraesCS5A01G400500 putatively involved in peroxidase activity was differently regulated in two haplotypes, with consistent sequence polymorphisms in the promoter region. Taken together, this study improved the accuracy of modelling simulation for contrasting genotypes, assessed the C and N allocation and NUE among different genotypes and investigated the potential genetic and physiological mechanisms. Further explorations were warranted to reveal the molecular mechanisms underlying ozone tolerance in wheat

On the investigation of hot tearing behavior of continuous cast steel

”Hot tearing has long been recognized as a major problem that plagues the development of the continuous casting process and results in low-quality products. Understanding of the mechanisms and the required conditions for the hot tearing formation is important for industries but has not been well-established yet. Thus, this research focuses on the hot tearing issue observed in continuous cast steel, by providing a summary of the current research progress and then introducing a new laboratory method to determine the thermo-mechanical properties relevant to hot tearing of different steel grades under different solidification conditions. In this method, an apparatus was developed to apply a certain amount of the strain to the solidifying steel shell at a controlled strain rate. A special mold, equipped with two water-cooled copper chills and an insulation sleeve, was designed to control the dendrite growth in the direction perpendicular to the applied strain and to ensure that the strain was applied in the region of controlled shell growth. The temperature, displacement and force were monitored and recorded as a function of time by a computer system during the test. The in-situ hot tensile test was performed for a medium carbon steel using this apparatus to determine the thermo-mechanical properties of the solidifying casting. Filling and solidification simulation software was used to predict the temperature profile during the experiment. It was found that the calculated temperature was in good agreement with the measured temperature in experiments. The fracture strength obtained with this method was comparable with that measured by the submerged-split chill tensile test, but was lower than that determined by the conventional hot tensile test”--Abstract, page iv

Towards Privacy and Security Concerns of Adversarial Examples in Deep Hashing Image Retrieval

With the explosive growth of images on the internet, image retrieval based on deep hashing attracts spotlights from both research and industry communities. Empowered by deep neural networks (DNNs), deep hashing enables fast and accurate image retrieval on large-scale data. However, inheriting from deep learning, deep hashing remains vulnerable to specifically designed input, called adversarial examples. By adding imperceptible perturbations on inputs, adversarial examples fool DNNs to make wrong decisions. The existence of adversarial examples not only raises security concerns for real-world deep learning applications, but also provides us with a technique to confront malicious applications. In this dissertation, we investigate privacy and security concerns in deep hashing image retrieval systems related to adversarial examples. Starting with a privacy concern, we stand on users side to preserve privacy information in images, which can be extracted by adversaries by retrieving similar images in image retrieval systems. Existing image processing-based privacy-preserving methods suffer from a trade-off of efficacy and usability. We propose a method introducing imperceptible adversarial perturbations on original images to prevent them from being retrieved. Users upload protected adversarial images instead of the original images to preserve privacy while maintaining usability. Then we shift to the security concerns. We act as attackers, proactively providing adversarial images to retrieval systems. These adversarial examples are embedded to specific targets so that the user retrieval results contain our unrelated adversarial images, e.g., users query with a “Husky dog” image, but retrieve adversarial “dog food” images in the result. A transferability-based attack is proposed for black-box models. We improve black-box transferability with the random noise as the proxy in optimization, achieving state-of-the-art success rate. Finally, we stand on retrieval systems side to mitigate the security concerns of adversarial attacks in deep hashing image retrieval. We propose a detection method that detects adversarial examples in the inference time. By studying unique adversarial behaviors in deep hashing image retrieval, our proposed method is constructed on criterions of these adversarial behaviors. The proposed method detects most of the adversarial examples with minimum overhead

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs' idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs' participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.Comment: 10 pages, 9 figure

DETERMINANTS OF BANK PROFITABILITY AND RISK-TAKING IN CHINA

By using the ordinary lease squares estimation technique, this paper examines the relationship between bank-specific characteristics together with macroeconomic factors, and profitability in Chinese banking sector. Therefore, to find out the how each factor affects the bank’s profitability. Moreover, this paper also uses three risk measures to analyze the banks’ business condition. The regression analysis is based on a panel data set consisting of 152 observations of 30Chinese banks over a 6-year period from 2011 to 2016.We found that for profitability, capital ratio and GDP growth rate have significant positive impacts and inflation rate has significant negative impact. Other independent variables do not have significant relationship with bank’s profitability. For risk, none of the independent variable has significant impact on Z-score and non-performing ratio; however, total deposits to total assets ratio and bank size have significant impact on non-interest income ratio