2,476 research outputs found
Supplemental Material - Pipeline fault simulation and control of a liquid rocket engine
No full textSupplemental Material for Pipeline fault simulation and control of a liquid rocket engine by Yuqiang Cheng, Runsheng Hu, and Jianjun Wu in Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering</p
Statistical methods for learning sparse features
No full textWith the fast development of networking, data storage, and the data collection capacity, big data are now rapidly expanding in all science and engineering domains. When dealing with such data, it is appealing if we can extract the hidden sparse structure of the data since sparse structures allow us to understand and interpret the information better. The aim of this thesis is to develop algorithms that can extract such hidden sparse structures of the data in the context of both supervised learning and unsupervised learning.
In chapter 1, this thesis first examines the limitation of the classical Fisher Discriminant Analysis (FDA), a supervised dimension reduction algorithm for multi-class classification problems. This limitation has been discussed by Cui (2012), and she has proposed a new objective function in her thesis, which is named Complementary Dimension Analysis (CDA) since each sequentially added new dimension boosts the discriminative power of the reduced space. A couple of extensions of CDA are discussed in this thesis, including sparse CDA (sCDA) in which the reduced subspace involves only a small fraction of the features, and Local CDA (LCDA) that handles multimodal data more appropriately by taking the local structure of the data into consideration. A combination of sCDA and LCDA is shown to work well with real examples and can return sparse directions from data with subtle local structures.
In chapter 2, this thesis considers the problem of matrix decomposition that arises in many real applications such as gene repressive identification and context mining. The goal is to retrieve a multi- layer low-rank sparse decomposition from a high dimensional data matrix. Existing algorithms are all sequential algorithms, that is, the first layer is estimated, and then remaining layers are estimated one by one, by conditioning on the previous layers. As discussed in this thesis, such sequential approaches have some limitations. A new algorithm is proposed to address those limitations, where all the layers are solved simultaneously instead of sequentially.
The proposed algorithm in chapter 2 is based on a complete data matrix. In many real applications and cross-validation procedures, one needs to work with a data matrix with missing values. How to operate the proposed matrix decomposition algorithm when there exist missing values is the main focus of chapter 3. The proposed solution seems to be slightly different from some existing work such as penalized matrix decomposition (PMD).
In chapter 4, this thesis considers a Bayesian approach to sparse principal component analysis (PCA). An efficient algorithm, which is based on a hybrid of Expectation-Maximization (EM) and Variational-Bayes (VB), is proposed and it can be shown to achieve selection consistency when both p and n go to infinity. Empirical studies have demonstrated the competitive performance of the proposed algorithm.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-08-10 without embargo termsThe student, Jianjun Hu, accepted the attached license on 2017-04-20 at 02:30.The student, Jianjun Hu, submitted this Dissertation for approval on 2017-04-20 at 02:38.This Dissertation was approved for publication on 2017-04-20 at 09:02.DSpace SAF Submission Ingestion Package generated from Vireo submission #10785 on 2017-08-10 at 13:40:45Made available in DSpace on 2017-08-10T19:15:08Z (GMT). No. of bitstreams: 3
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Previous issue date: 2017-04-2
Lubrication of rough copper with few-layer graphene
No full textIt has been demonstrated through experiments and simulations that friction decreases significantly when graphene is used as a solid lubricant on various materials. However, the effect of increasing the number of graphene layers on lubrication is controversial. Some studies predict an increase of friction with the number of layers that can be imputed to increased contact area, others a decrease in friction attributed to increased flexural rigidity of the layers. Herein, atomistic simulations are performed to investigate the atomic mechanisms by which few-layers graphene lubricate rough copper surfaces when probed by a smooth tip. The results of the simulations show that increasing the number of graphene layers drastically reduces friction, while the deformation mechanism is found to change from atomic wear to recoverable flattening of surface steps, as the amount of interlocking between the surfaces is reduced.Team Marcel Sluite
USPTO 2M USA Patent information dataset
No full textUSPTO-2M is a dataset which download from United State Patent Trademark Office. It contains 2 million records which have cleaned and organized into JSON format.It could work as a benchmark dataset for patent classification task.Provided by Jie Hu from Guzhou University of Finance and Economics and Dr. Jianjun Hu at University of South Carolina.Citation: Li, Shaobo, Jie Hu, Yuxin Cui, and Jianjun Hu. "DeepPatent: patent classification with convolutional neural networks and word embedding." Scientometrics 117 (2018): 721-744.a sample of our data. { "Subclass_labels": [ "A43B", "A41D", "A43C" ], "Abstract": "a decorative and or promotional accessory to be secured to a lace such as a shoe lace includes a molded plastic body having a passage longitudinally extending therethrough from a first opening to a second opening the passage is sized and shaped to receive the lace therethrough and to frictionally secure the body in a desired position along the lace the accessory also includes indicia provided on an exterior surface of the accessory which can be in the form of any desired message name number logo graphic or the like an alternative embodiment of the accessory is disclosed which is to be secured to a cap bill this embodiment includes a slot radially extending to the passage which is sized and shaped to receive the cap brim therein and to resiliently grip the bill and removably secure the accessory in a desired position along the bill", "Title": "accessory for shoe laces hat brims and the like", "No": "US08925116" }</p
sj-pdf-1-ang-10.1177_00033197221082712 – Supplemental Material for Long-Term Blood Pressure Exposure From Childhood and Early Vascular Aging in Midlife: A 30-Year Prospective Cohort Study
No full textSupplemental Material, sj-pdf-1-ang-10.1177_00033197221082712 for Long-Term Blood Pressure Exposure From Childhood and Early Vascular Aging in Midlife: A 30-Year Prospective Cohort Study by Yu Yan, Yu Cao, Qiong Ma, Keke Wang, Yueyuan Liao, Yue Sun, Chen Chen, Jiawen Hu, Wenling Zheng, Chao Chu, Yang Wang, and Jianjun Mu in Angiology</p
Supplemental Material - Association Between Serum Uric Acid and Abdominal Aortic Calcification in Adults Aged 40 to 80 years: A Retrospective Cross-Sectional Study
No full textSupplemental Material for Association Between Serum Uric Acid and Abdominal Aortic Calcification in Adults Aged 40 to 80 years: A Retrospective Cross-Sectional Study by Sheng Hu, Shengyu Qiu, Bingen Wan, Liancheng Ruan, Lingxiao Zhu, Siling Wang, Lang Su, Qiang Guo, Jianjun Xu and Yiping Wei in Journal of Angiology.</p
sj-docx-1-npx-10.1177_1934578X221095350 - Supplemental material for Comparison of Chemical Compositions and Antioxidant Activities of Fresh and Dried <i>Rosa roxburghii</i> Tratt Fruit
No full textSupplemental material, sj-docx-1-npx-10.1177_1934578X221095350 for Comparison of Chemical Compositions and Antioxidant Activities of Fresh and Dried Rosa roxburghii Tratt Fruit by Guanyu Yan, Peiyan Zheng, Shaoquan Weng, Yida Zhang, Wenliu Xu, Jiaying Luo, Jianjun Fei, Jingxian Wang, Hui Zhang, Haisheng Hu and Baoqing Sun in Natural Product Communications</p
sj-docx-1-tct-10.1177_15330338211049903 - Supplemental material for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma
No full textSupplemental material, sj-docx-1-tct-10.1177_15330338211049903 for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma by Weibiao Zeng, Wen Zheng, Sheng Hu, Jianyong Zhang, Wenxiong Zhang, Jianjun Xu, Dongliang Yu, Jinhua Peng, Lu Zhang, Meng Gong and Yiping Wei in Technology in Cancer Research & Treatment</p
sj-pdf-3-tct-10.1177_15330338211049903 - Supplemental material for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma
No full textSupplemental material, sj-pdf-3-tct-10.1177_15330338211049903 for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma by Weibiao Zeng, Wen Zheng, Sheng Hu, Jianyong Zhang, Wenxiong Zhang, Jianjun Xu, Dongliang Yu, Jinhua Peng, Lu Zhang, Meng Gong and Yiping Wei in Technology in Cancer Research & Treatment</p
sj-pdf-2-tct-10.1177_15330338211049903 - Supplemental material for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma
No full textSupplemental material, sj-pdf-2-tct-10.1177_15330338211049903 for Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma by Weibiao Zeng, Wen Zheng, Sheng Hu, Jianyong Zhang, Wenxiong Zhang, Jianjun Xu, Dongliang Yu, Jinhua Peng, Lu Zhang, Meng Gong and Yiping Wei in Technology in Cancer Research & Treatment</p
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