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2,336 results on '"Wu Qinghua"'

60. Exploiting Deep Sentential Context for Expressive End-to-End Speech Synthesis

Author

Yang, Fengyu, Yang, Shan, Wu, Qinghua, Wang, Yujun, and Xie, Lei

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
Abstract

Attention-based seq2seq text-to-speech systems, especially those use self-attention networks (SAN), have achieved state-of-art performance. But an expressive corpus with rich prosody is still challenging to model as 1) prosodic aspects, which span across different sentential granularities and mainly determine acoustic expressiveness, are difficult to quantize and label and 2) the current seq2seq framework extracts prosodic information solely from a text encoder, which is easily collapsed to an averaged expression for expressive contents. In this paper, we propose a context extractor, which is built upon SAN-based text encoder, to sufficiently exploit the sentential context over an expressive corpus for seq2seq-based TTS. Our context extractor first collects prosodic-related sentential context information from different SAN layers and then aggregates them to learn a comprehensive sentence representation to enhance the expressiveness of the final generated speech. Specifically, we investigate two methods of context aggregation: 1) direct aggregation which directly concatenates the outputs of different SAN layers, and 2) weighted aggregation which uses multi-head attention to automatically learn contributions for different SAN layers. Experiments on two expressive corpora show that our approach can produce more natural speech with much richer prosodic variations, and weighted aggregation is more superior in modeling expressivity., Comment: Accepted by Interspeech2020

Published
2020

61. Solving the Clustered Traveling Salesman Problem via TSP methods

Author

Lu, Yongliang, Hao, Jin-Kao, and Wu, Qinghua

Subjects
Computer Science - Artificial Intelligence
Abstract

The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular Traveling Salesman Problem (TSP) arising from a number of real-life applications. In this work, we explore a transformation approach that solves the CTSP by converting it to the well-studied TSP. For this purpose, we first investigate a technique to convert a CTSP instance to a TSP and then apply powerful TSP solvers (including exact and heuristic solvers) to solve the resulting TSP instance. We want to answer the following questions: How do state-of-the-art TSP solvers perform on clustered instances converted from the CTSP? Do state-of-the-art TSP solvers compete well with the best performing methods specifically designed for the CTSP? For this purpose, we present intensive computational experiments on various benchmark instances to draw conclusions., Comment: 26 pages, 6 figures

Published
2020

62. Cross-layer Path Selection in Multi-path Transport Protocol for Mobile Devices

Author

Liao, Binbin, Zhang, Guangxing, Wu, Qinghua, Li, Zhenyu, and Xie, Gaogang

Subjects
Computer Science - Networking and Internet Architecture
Abstract

MPTCP is a new transport protocol that enables mobile devices to use multiple physical paths simultaneously through several network interfaces, such as WiFi and Cellular. However, wireless path capacities change frequently in the mobile environments, causing challenges for path selection. For example, WiFi associated paths often become poor as devices walk away, since WiFi has intermittent connectivity caused by the short signal coverage and stochastic interference. MPTCP's native decision based on hysteretic TCP-layer estimation will miss the real switching point of wireless quality, which may cumulate packets on the broken path and causes serious packets reinjection. Through analyzing a unique dataset in the wild, we quantitatively study the impact of MAC-layer factors on the aggregated performance of MPTCP. We then propose a decision tree approach for cross-layer path selection that decides which path to carry the incoming packets dynamically according to the prior learned schemes. A prototype of the path selection system named SmartPS, which proactively probes the wireless environments, is realized and deployed in Linux and Android. Evaluation results demonstrate that our SmartPS can efficiently utilize the faster path, with goodput improvements of up to 29%., Comment: ICNP under review

Published
2020

65. Effects of metastasis-associated in colon cancer 1 inhibition by small hairpin RNA on ovarian carcinoma OVCAR-3 cells

Author

Ren Fang, Wu Qinghua, Chen Zhimin, Shi Huirong, Zhang Ruitao, and Huang Haoliang

Subjects
Ovarian carcinoma OVCAR-3 cells, Metastasis-associated in colon cancer 1, Small hairpin RNA, Therapy target, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Metastasis-associated in colon cancer 1 (MACC1) is demonstrated to be up-regulated in several types of cancer, and can serve as biomarker for cancer invasion and metastasis. To investigate the relations between MACC1 and biological processes of ovarian cancer, MACC1 specific small hairpin RNA (shRNA) expression plasmids were used to investigate the effects of MACC1 inhibition on ovarian carcinoma OVCAR-3 cells. Methods Expressions of MACC1 were detected in different ovarian tissues by immunohistochemistry. MACC1 specific shRNA expression plasmids were constructed and transfected into OVCAR-3 cells. Then, expressions of MACC1 were examined by reverse transcription polymerase chain reaction (RT-PCR) and Western blot. Cell proliferation was observed by MTT and monoplast colony formation assay. Flow cytometry and TUNEL assay were used to measure cell apoptosis. Cell migration was assessed by wound healing and transwell migration assay. Matrigel invasion and xenograft model assay were performed to analyze the potential of cell invasion. Activities of Met, MEK1/2, ERK1/2, Akt, cyclinD1, caspase3 and MMP2 protein were measured by Western blot. Results Overexpressions of MACC1 were detected in ovarian cancer tissues. Expression of MACC1 in OVCAR-3 cells was significantly down-regulated by MACC1 specific small hairpin RNA. In OVCAR-3 cells, down-regulation of MACC1 resulted in significant inhibition of cell proliferation, migration and invasion, meanwhile obvious enhancement of apoptosis. As a consequence of MACC1 knockdown, expressions of Met, p-MEK1/2, p-ERK1/2, cyclinD1 and MMP2 protein decreased, level of cleaved capase3 was increased. Conclusions RNA interference (RNAi) against MACC1 could serve as a promising intervention strategy for gene therapy of ovarian carcinoma, and the antitumor effects of MACC1 knockdown might involve in the inhibition of HGF/Met and MEK/ERK pathways.

Published
2011
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76. DNA methylation profiling of ovarian carcinomas and their in vitro models identifies HOXA9, HOXB5, SCGB3A1, and CRABP1 as novel targets

Author

Tropé Claes G, Silins Ilvars, Ahlquist Terje, Lothe Ragnhild A, Wu Qinghua, Micci Francesca, Nesland Jahn M, Suo Zhenhe, and Lind Guro E

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background The epigenetics of ovarian carcinogenesis remains poorly described. We have in the present study investigated the promoter methylation status of 13 genes in primary ovarian carcinomas (n = 52) and their in vitro models (n = 4; ES-2, OV-90, OVCAR-3, and SKOV-3) by methylation-specific polymerase chain reaction (MSP). Direct bisulphite sequencing analysis was used to confirm the methylation status of individual genes. The MSP results were compared with clinico- pathological features. Results Eight out of the 13 genes were hypermethylated among the ovarian carcinomas, and altogether 40 of 52 tumours were methylated in one or more genes. Promoter hypermethylation of HOXA9, RASSF1A, APC, CDH13, HOXB5, SCGB3A1 (HIN-1), CRABP1, and MLH1 was found in 51% (26/51), 49% (23/47), 24% (12/51), 20% (10/51), 12% (6/52), 10% (5/52), 4% (2/48), and 2% (1/51) of the carcinomas, respectively, whereas ADAMTS1, MGMT, NR3C1, p14ARF, and p16INK4a were unmethylated in all samples. The methylation frequencies of HOXA9 and SCGB3A1 were higher among relatively early-stage carcinomas (FIGO I-II) than among carcinomas of later stages (FIGO III-IV; P = 0.002, P = 0.020, respectively). The majority of the early-stage carcinomas were of the endometrioid histotype. Additionally, HOXA9 hypermethylation was more common in tumours from patients older than 60 years of age (15/21) than among those of younger age (11/30; P = 0.023). Finally, there was a significant difference in HOXA9 methylation frequency among the histological types (P = 0.007). Conclusion DNA hypermethylation of tumour suppressor genes seems to play an important role in ovarian carcinogenesis and HOXA9, HOXB5, SCGB3A1, and CRABP1 are identified as novel hypermethylated target genes in this tumour type.

Published
2007
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