1,725,854 research outputs found
Interview with Mei Ling Wong, Joon Xiong, and David Xiong (Sushi Hut)
Get PDFMei-Ling Wong is a second-generation Chinese American who was born in Kunming, Yunnan in China. Mei Ling moved to this country and met her husband Joon Xiong who was born in the same region. They both have been working in the restaurant business for the past 30 years. For the last 20 years, they have been working together in different types of restaurants in the Monterey bay area. In 2018 they decide to open their own restaurant named ``Sushi Hut \u27\u27 and by applying all the knowledge they have developed in the past years, they build a menu with a mixture of different traditional recipes from Japan and China culture.https://digitalcommons.csumb.edu/asia-pacific-foodways_interviews/1009/thumbnail.jp
Serum apolipoprotein AI and B in adult-onset type diabetes among the local Chinese population.
Get PDFby Yuen Mei Ling, Miranda.Thesis (M.Sc.)--Chinese University of Hong Kong, 1989.Bibliography: leaves 73-83
New Roads for Patron-Driven E-books:Collection Development and Technical Services Implications of a Patron-Driven Acquisitions Pilot at Rutgers
No full textCollection development librarians have long struggled to meet user demands for new titles. Too often, required resources are not purchased, while some purchased resources do not circulate. E-books selected through patron-driven plans are a solution but present new challenges for both selectors and catalogers. Radical changes to traditional technical services workflows are required, and selectors must modify the selection process to give more choice to the user. Rutgers University librarians have adopted an innovative new technical services workflow and collection-development model to manage a successful, patron-driven acquisitions project for e-books in the fields of math and computer science.This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Electronic Resources Librarianship on 13/12/2011, available online at: http://www.tandfonline.com/10.1080/1941126X.2011.627043
Chiang Kai-shek avant Soon Mei-ling [Chiang Kai-sheks Secret Past, de Ch'en Chieh-ju]
No full textCorcuff Stéphane. Chiang Kai-shek avant Soon Mei-ling [Chiang Kai-sheks Secret Past, de Ch'en Chieh-ju]. In: Perspectives chinoises, n°29, 1995. pp. 68-70
Chiang Kai-shek avant Soon Mei-ling [Chiang Kai-sheks Secret Past, de Ch'en Chieh-ju]
No full textCorcuff Stéphane. Chiang Kai-shek avant Soon Mei-ling [Chiang Kai-sheks Secret Past, de Ch'en Chieh-ju]. In: Perspectives chinoises, n°29, 1995. pp. 68-70
The use of distinctive features for automatic speech recognition
No full textThesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.by Helen Mei-Ling Meng.M.S
Computer Applications in Land Use Mapping and the Minnesota Land Management Information System.
Get PDFHsu, Mei Ling et al.. (1973). Computer Applications in Land Use Mapping and the Minnesota Land Management Information System.. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/205789
Yan Hairong, New Masters, New Servants : Migration, Development, and Women Workers in China,
Get PDFEllerman Mei-Ling. Yan Hairong, New Masters, New Servants : Migration, Development, and Women Workers in China, . In: Perspectives chinoises, n°110, 2010. pp. 137-139
Data quality enhancement and knowledge discovery from relevant signals in acoustic emission
No full textThe increasing popularity of structural health monitoring has brought with it a growing need for automated data management and data analysis tools. Of great importance are filters that can systematically detect unwanted signals in acoustic emission datasets. This study presents a semi-supervised data mining scheme that detects data belonging to unfamiliar distributions. This type of outlier detection scheme is useful detecting the presence of new acoustic emission sources, given a training dataset of unwanted signals. In addition to classifying new observations (herein referred to as "outliers") within a dataset, the scheme generates a decision tree that classifies sub-clusters within the outlier context set. The obtained tree can be interpreted as a series of characterization rules for newly-observed data, and they can potentially describe the basic structure of different modes within the outlier distribution. The data mining scheme is first validated on a synthetic dataset, and an attempt is made to confirm the algorithms' ability to discriminate outlier acoustic emission sources from a controlled pencil-lead-break experiment. Finally, the scheme is applied to data from two fatigue crack-growth steel specimens, where it is shown that extracted rules can adequately describe crack-growth related acoustic emission sources while filtering out background "noise." Results show promising performance in filter generation, thereby allowing analysts to extract, characterize, and focus only on meaningful signals
Photograph of various dignitaries with Generalissimo Chiang Kai-shek and Madame Soong Mei-ling
No full textBlack and white photograph. Various dignitaries with Generalissimo Chiang Kai-shek and Madame Soong Mei-ling (center). Kika de la Garza and wife Lucille are second and third on the first row from the right. The rest are unknown dignitaries.https://scholarworks.utrgv.edu/kikadelagarzaphotographs/1114/thumbnail.jp
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