Data Mining Analysis of the Parkinson\u27s Disease

Biological research is becoming increasingly database driven and statistical learning can be used to discover patterns in the biological data. In the thesis, the supervised learning approaches are utilized to analyze the Oxford Parkinson’s disease detection data and build models for prediction or classification. We construct predictive models based on training set, evaluate their performance by applying these models to an independent test set, and find the best methods for predicting whether people have Parkinson’s disease. The proposed artificial neural network procedure outperforms with the best and highest prediction accuracy, while the logistic and probit regressions are preferred statistical models which can offer better interpretation with the higher prediction accuracy compared to other proposed data mining approaches

On the nonintegrability of equations for long- and short-wave interactions

We examine the integrability of two models used for the interaction of long and short waves in dispersive media. One is more classical but arguably cannot be derived from the underlying water wave equations, while the other one was recently derived. We use the method of Zakharov and Schulman to attempt to construct conserved quantities for these systems at different orders in the magnitude of the solutions. The coupled KdV-NLS model is shown to be nonintegrable, due to the presence of fourth-order resonances. A coupled real KdV - complex KdV system is shown to suffer the same fate, except for three special choices of the coefficients, where higher-order calculations or a different approach are necessary to conclude integrability or the absence thereof.Comment: 9 pages, presented as a poster at The Tenth IMACS International Conference on Nonlinear Evolution Equations and Wave Phenomena: Computation and Theor

Infinite series identities involving quadratic and cubic harmonic numbers

By means of the modified Abel lemma on summation by parts, we investigate infinite series involving quadratic and cubic harmonic numbers. Several infinite series identities are established for π 2 and ζ(3) as consequences

Cyclist’s Intention Identification on Pedestrian-Bicycle Mixed Sections Based on Phase-Field Coupling Theory

Bicycle is one of the main factors that affects the traffic safety and capacity on pedestrian-bicycle mixed traffic sections. It is important for implementing the warning of bicycle safety and improving the active safety to identify the cyclists’ intention in the mixed traffic environments under the condition of the “Internet of Things”. The phase-field coupling theory has been developed in this paper to comprehensively analyse the generation, spring up, increase, transfer, regression and reduction method of the traffic phase. The adaptive genetic algorithm based on the information entropy has been used to extract feature vectors of different types of cyclists for intention identification from the reduced pedestrian-bicycle traffic phase, and the theory of evidence has been provided here to build the identification model. The experimental verification shows that the extraction method of cyclists’ intention feature vector and identification model are scientific and reasonable. The theoretical basis can be applied to establishing the pedestrian-bicycle interactive security system.</p

A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction

In spite of its importance, passenger demand prediction is a highly challenging problem, because the demand is simultaneously influenced by the complex interactions among many spatial and temporal factors and other external factors such as weather. To address this problem, we propose a Spatio-TEmporal Fuzzy neural Network (STEF-Net) to accurately predict passenger demands incorporating the complex interactions of all known important factors. We design an end-to-end learning framework with different neural networks modeling different factors. Specifically, we propose to capture spatio-temporal feature interactions via a convolutional long short-term memory network and model external factors via a fuzzy neural network that handles data uncertainty significantly better than deterministic methods. To keep the temporal relations when fusing two networks and emphasize discriminative spatio-temporal feature interactions, we employ a novel feature fusion method with a convolution operation and an attention layer. As far as we know, our work is the first to fuse a deep recurrent neural network and a fuzzy neural network to model complex spatial-temporal feature interactions with additional uncertain input features for predictive learning. Experiments on a large-scale real-world dataset show that our model achieves more than 10% improvement over the state-of-the-art approaches.Comment: https://epubs.siam.org/doi/abs/10.1137/1.9781611975673.1

Essays on Consumer Behavior and Demand Analysis

The thesis consists of two loosely related essays. Both are motivated by consumers’ behavior regularities in different market environments. My goal is to show evidence of behavioral biases among decision makers and the consequences of those behavioral effects. Given each market’s environment, I found evidence that consumers tend to deviate from what conventional theories dictate and the deviation may affect welfare analysis. The first market is a non-durable experience good market. Using empirical scanner data,we show evidence that consumers’ switching rates among brands are higher than what brand characteristics and consumer heterogeneity can explain. The over-switching behavior may be consistent with consumers’ brand satiation. As a result, the consumers may benefit more from a market with more variety. We provide a structural model of the satiation behavior and use the model to demonstrate the model prediction as well as the welfare effect. The second market is a laboratory sequential search market where sellers are allowed to use exploding offers. We show evidence that buyers may be affected by non-monetary incentives, which result in a higher rejection rate for the exploding offers. After accounting for the above mentioned “exploding offer aversion”, sellers’ optimal strategies may be shifted. As a result, sellers tend to use lower price as well as non-exploding offers more often

Welche Lehrwerke für welche Kultur?

Viele junge Chinesinnen und Chinesen bereiten sich auf einen Aufenthalt in deutschsprachigen Ländern vor. Dafür erlernen sie – teils neben dem Studium oder dem Berufsalltag – Deutsch als Fremdsprache in China. Welche Lehrwerke werden dort eingesetzt? Auffällig ist die Rückkehr zu einheimischen Lehrwerken in deutschen Vorbereitungskursen der chinesischen Universitäten und Hochschulen in den letzten Jahren. Die vorliegende Untersuchung zielt darauf ab, die Gründe für diese Rückkehr und die Einflussfaktoren bei der Lehrwerkauswahl zu erschließen. Mein besonderes Erkenntnisinteresse gilt der Frage, ob die Lehrwerke, die in Deutschland entwickelt werden, auf China, wo andere soziokulturelle Rahmenbedingungen gelten, übertragbar sind? Diese Lehrwerke verfolgen die methodischen und didaktischen Prinzipien, die sich in Deutschland durchsetzen. Passen sie auch für China? Konkreter formuliert: unter welchen Bedingungen können die neuen didaktischen oder methodischen Gedanken bzw. die diesen folgenden Lehrwerke in der Praxis umgesetzt werden? Diese Forschungsfragen werden durch Interviews mit solchen Experten beantwortet, die die Entscheidung der Lehrwerkauswahl für den untersuchten Kurs beeinflussen können. Die durch die Experteninterviews erhobenen Daten werden nach der qualitativen Inhaltsanalyse des Kuckartzschen Konzepts ausgewertet. Aus der Analyse ergibt sich, dass im Gegensatz zu der zentralen Bedeutung der Lernerorientierung bei der Lehrwerkuntersuchung im deutschen Raum eine entscheidende Bedeutung dem Faktor der Berücksichtigung der Lehrgewohnheit zukommt. Zur Durchsetzung der neuen didaktischen und methodischen Gedanken im Unterricht spielen die Ansichten der Lehrenden darüber eine wichtige bis entscheidende Rolle. Eine weitere erforderliche Bedingung ist, dass die Lehrenden sich Autorität verschaffen müssen. Dann sind die Lernenden bereit, sich umzuorientieren. Sinnvoll wäre, in weiteren Untersuchungen mehr auf die Interaktion zwischen einem Lehrwerk und den Lehrenden bzw. die Angemessenheit eines Lehrwerks für bestimmte Lehrende, beispielsweise Lehrende einer bestimmten Kultur, einzugehen

翻译、意识形态与话语 : 中国1895-1911 年文学翻译研究

1895－1911 年这一时期，是中国翻译史上第三次翻译高潮。现有的中国翻译史研究成果，由于受到各自的研究对象以及研究者自身的局限，均未能对这一断代史进行充分的研究。本文采取文化研究的视角，尝试建立一个新的理论模式――翻译社会学模式，即考察翻译场域中，翻译这一话语生产活动，如何在受到意识形态制约的 同时，通过不同途径（其中特别是通过主体性）获得各种资本，尤其是符号象征资本，对现有意识形态（尤其是主流意识形态）产生作用。在此基础上，对这一时期的文学翻译，特别是小说的翻译，加以研究。 本文认为：翻译这一社会行为，不仅是语言之间而是处在特定的历史语境之中的转换活动，因而势必会受到当时意识形态的制约；同时，翻译作为一种话语生产活动，亦会因此生产新的意识形态话语。由此，翻译与意识形态之间存在着一种互动关系。 本文采取纵横相结合的方法：首先从纵的即历史的跨度，考察这一时期翻译行为所处的社会文化语境，从文化史与思想史的高度，概述这一时期的翻译史特征，史论结合，以史为辅，以论为主。其次，截取其中某个时间横断面，对这一时期具有代表性的论者与译者，进行深入的个案分析（包括梁启超、林 纾、苏曼殊、周氏兄弟），希冀通过以点带面的方式，微观（文本分析）与宏观（文化研究）相结合，以微见著，从微观中看出宏观来，同时又能高屋建瓴， 从宏观解释微观，总结该时期的翻译活动的特征与规律