892 research outputs found
Hong wu shi
No full text王家齊著.本電子書乃根據《香港版權條例(第528章)》而複製, 並只可在大學圖書館系統內的獨立電子書系統上使用.Wang Jiaqi zhu.Ben dian zi shu nai gen ju "Xianggang ban quan tiao li (Di 528 zhang)" er fu zhi, bing zhi ke zai da xue tu shu guan xi tong nei de du li dian zi shu xi tong shang shi yong
Deciphering the heterogeneity and spatial architecture of tumors
No full textCancer is caused by the accumulation of somatic mutations that form distinct populations of cells, called clones. The resulting intra-tumor heterogeneity evolves temporally, as well as spatially, and is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cancer genomics datasets that effectively capture mutational signals in cancer have become available, allowing researchers to closely examine the underlying mechanisms that shape the tumor landscape. In this thesis, we explore the multi-faceted elements of intra-tumor heterogeneity via visualization, quantification, and detection. We begin by introducing ClonArch, a tool which interactively visualizes the evolutionary relationships and spatial distribution of clones in a single tumor mass. ClonArch fills the gap for visualizations that address spatial aspects of clonal architecture. We then adapt a cancer genomics pipeline to quantify intra-tumor heterogeneity in a porcine model, showing its potential impact on translational clinical studies. Finally, we attempt to detect negative selection in the cancer exome by performing a depletion analysis on neoantigens.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01The student, Jiaqi Wu, accepted the attached license on 2020-05-11 at 17:52.The student, Jiaqi Wu, submitted this Thesis for approval on 2020-05-11 at 18:47.This Thesis was approved for publication on 2020-05-12 at 14:18.DSpace SAF Submission Ingestion Package generated from Vireo submission #15338 on 2020-08-25 at 17:31:00Made available in DSpace on 2020-08-26T23:58:46Z (GMT). No. of bitstreams: 2
WU-THESIS-2020.pdf: 3017251 bytes, checksum: b01b13f920a8bc08c7c7c46943562a51 (MD5)
LICENSE.txt: 4205 bytes, checksum: 2b865e1b5a043951de7f101ad3f12ead (MD5)
Previous issue date: 2020-05-12Embargo set by: Seth Robbins for item 115798
Lift date: 2022-08-26T23:58:55Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Sylviane Granger and Marie-Aude Lefer: Extending the Scope of Corpus-based Translation Studies (London: Bloomsbury, 2022. 274 pages)
No full textFang Tang: Explicitation in Consecutive Interpreting (Amsterdam and Philadelphia: John Benjamins, 2018. 237 pages)
No full textConnected Marysville pilot analysis--phase 1 : final report
No full text"Author(s), Timcho, Thomas -- WSP; Byington, Cynthia -- MurphyEpson; Ma, Dr. Jiaqi -- University of Cincinnati; Keister, Marie -- MurphyEpson"--Technical report documentation page.; "October 2018."; "FHWA/OH-2019-2"--Technical report documentation page.; Final report.; Sponsoring agency: Ohio Department of Transportation; State Job Number 135765Final report (5 unnumbered preliminary pages, 26 pages).This report summarizes the outcomes of phase 1 of the Connected Marysville Pilot Analysis project and includes a deployment plan, technology summary, design of experiment and recruitment plan. It is expected to serve as the foundation for the next phase of the project, the recruitment and deployment of connected vehicle technology in 400 private citizen vehicles in the City of Marysville, OH
AAEC: An Adversarial Autoencoder-based Classifier for Audio Emotion Recognition
No full textChangzeng Fu, Jiaqi Shi, Chaoran Liu, Carlos Toshinori Ishi, and Hiroshi Ishiguro. 2020. AAEC: An Adversarial Autoencoder-based Classifier for Audio Emotion Recognition. In Proceedings of the 1st International on Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop (MuSe'20). Association for Computing Machinery, New York, NY, USA, 45–51. DOI:https://doi.org/10.1145/3423327.3423669.MM '20: The 28th ACM International Conference on Multimedia [October 16, 2020]In recent years, automatic emotion recognition has attracted the attention of researchers because of its great effects and wide implementations in supporting humans' activities. Given that the data about emotions is difficult to collect and organize into a large database like the dataset of text or images, the true distribution would be difficult to be completely covered by the training set, which affects the model's robustness and generalization in subsequent applications. In this paper, we proposed a model, Adversarial Autoencoder-based Classifier (AAEC), that can not only augment the data within real data distribution but also reasonably extend the boundary of the current data distribution to a possible space. Such an extended space would be better to fit the distribution of training and testing sets. In addition to comparing with baseline models, we modified our proposed model into different configurations and conducted a comprehensive self-comparison with audio modality. The results of our experiment show that our proposed model outperforms the baselines
隠遁の祖・許由の図像について
No full textXu You was a legendary Chinese hermit. After refusing the emperor Yao’s offer of the royal throne, he washed out his ears in abashed. Another hermit Chao Fu passed by, and forbidden his cow to drink from the water, because of Xu had contaminating it. Xu’s virtue was highly appreciated in Asian culture. His iconography was wildly used in art works like bronze mirrors, lacquerware, ceramic, paintings and architecture. Despite Xu’s popularity in Asia, Chinese and Japanese have different ways of appreciation. In China, Xu is regarded as the archetype of virtue hermit, who refused to be the ruler in power. While in Japan, Xu’s interaction with Chao is preferred, especially in literature, paintings and architecture. However, there are certain types of Xu’s iconography remains unidentified or misidentified. This study aims at identifying Xu You’s iconography in Asian art, and tried to uncover the reason why certain types of iconographies are popular in particular dynasty and region
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