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IEEE International Conference on Advanced Management Science (ICAMS)

作者： Jing Zhang Liuqi Ye Business School Hohai University HHU Nanjing Jiangsu China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing China

This article has been retracted by the publisher.

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Unveiling Funded Research: Impact and Dual Innovation

SSRN

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SSRN 2023年

作者： Yang, Alex Jie School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China International Joint Informatics Laboratory Nanjing University Nanjing210023 China

In the relentless pursuit of scientific advancement, comprehending the profound impact and innovation nature inherent in funded research projects assumes paramount significance. To illuminate this matter, I delve into the realm of research supported by the esteemed National Institutes of Health (NIH) and the distinguished National Science Foundation (NSF). Our evaluative framework encompasses a spectrum of metrics, including the 5-year citation, normalized citation, and citation to patents, as markers of research impact. Moreover, I embrace ex-ante innovation (Novelty) and ex-post innovation (Disruption) as dual indispensable yardsticks for evaluating the innovative nature of research projects. Novelty denotes the manifestation of atypical combinations of existing knowledge, while Disruption signifies the extent of paradigm-shifting potential and the ability to exert a disruptive influence on future research endeavors. First, the analysis reveals that funded research projects manifest a conspicuously heightened impact in comparison to their non-funded counterparts. Second, I uncover a noteworthy finding, namely that funded research demonstrates significantly higher levels of ex-ante innovation (Novelty). However, in a surprising twist, the investigation also uncovers that funded research exhibits significantly lower levels of ex-post innovation (Disruption). Additionally, I undertake a meticulous scrutiny of the robustness of the research findings by scrutinizing patterns across disparate years and fields. This comprehensive analysis further unveils inconspicuous heterogeneity, thus substantiating the multifaceted nature of funded research and the vast potential for its innovation across various disciplines and temporal dimensions. © 2023, The Authors. All rights reserved.

关键词： Patents and inventions

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Joint multi-task cascade for instance segmentation

Joint multi-task cascade for instance segmentation

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作者： Wen, Yaole Hu, Fuyuan Ren, Jinchang Shang, Xinru Li, Linyan Xi, Xuefeng School of Electronic & Information Engineering Suzhou University of Science and Technology SuzhouJiangsu215009 China Centre for Signal and Image Processing University of Strathclyde Glasgow United Kingdom Suzhou Institute of Trade & Commerce SuzhouJiangsu215009 China Virtual Reality Key Laboratory of Intelligent Interaction and Application Technology of Suzhou Suzhou University of Science and Technology SuzhouJiangsu215009 China Suzhou Key Laboratory for Big Data and Information Service Suzhou University of Science and Technology SuzhouJiangsu215009 China

Instance segmentation requires both pixel-level classification accuracy and high-level semantic features at the target instance level, which is very challenging, and the cascade structure can effectively improve both of these problems. To make full use of the relationship between detection and segmentation, this paper proposes a joint multi-tasking cascade structure, which is not simply to cascade the two tasks of detection and segmentation, but to unitedly put them into multi-stage processing, and especially to integrate the information at different stages of the mask branch. The entire structure can effectively utilize the superior characteristics of each stage in the matter of detection and segmentation, thus improving the quality of mask prediction. The feature fusion process is introduced in the full convolution networks (FCN) branch, and the high-level and low-level features are effectively fused to enhance the contextual information of the picture semantic features. The experiments demonstrate the better results on the COCO dataset. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Semantics

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Notice of Retraction: System Formulation of knowledge Sharing and Exchange in the Organization

Notice of Retraction: System Formulation of Knowledge Sharin...

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International Conference on Management and service Science, MASS

作者： Jing Zhang Liuqi Ye Business School Hohai University HHU Nanjing Jiangsu China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing China

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Chinese Idiom Paraphrasing

arXiv

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arXiv 2022年

作者： Qiang, Jipeng Li, Yang Zhang, Chaowei Li, Yun Yuan, Yunhao Zhu, Yi Wu, Xindong School of Information Engineering Yangzhou University Jiangsu Yangzhou China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Anhui Hefei China

Idioms, are a kind of idiomatic expression in Chinese, most of which consist of four Chinese characters. Due to the properties of non-compositionality and metaphorical meaning, Chinese Idioms are hard to be understood by children and non-native speakers. This study proposes a novel task, denoted as Chinese Idiom Paraphrasing (CIP). CIP aims to rephrase idioms-included sentences to non-idiomatic ones under the premise of preserving the original sentence’s meaning. Since the sentences without idioms are easier handled by Chinese NLP systems, CIP can be used to pre-process Chinese datasets, thereby facilitating and improving the performance of Chinese NLP tasks, e.g., machine translation system, Chinese idiom cloze, and Chinese idiom embeddings. In this study, CIP task is treated as a special paraphrase generation task. To circumvent difficulties in acquiring annotations, we first establish a large-scale CIP dataset based on human and machine collaboration, which consists of 115,530 sentence pairs. We further deploy three baselines and two novel CIP approaches to deal with CIP problems. The results show that the proposed methods have better performances than the baselines based on the established CIP dataset. © 2022, CC BY.

关键词： Natural language processing systems

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Research Progress of CDT 19

Research Progress of CDT

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Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science

作者： Gao Yuting Shen Shutong Deng Sanhong School of Information Management Nanjing University China School of Information Management Nanjing University China Key Laboratory of Data Engineering and Knowledge Services in Jiangsu Province

ISBN: (纸本)9781450372510

With the high mortality rate for the cases of malignant tumors, the discovery and early treatment of cancer is critical to improving the 5-year survival rate of cancer. The biggest challenge in control and prevention is how to detect tumors as early as possible, so that the most effective means can be used for treatment. With the help of the WOS database, researchers found that liquid biopsy, genetic material/protein expression and computer imaging play an important role in cancer detection. Through analysis of the history and current status of cancer detection technology development, this paper also aims to provide guidance for the clinical practice of current cancer screening and provide inspiration for future technological development.

关键词： Biopharmaceutical engineering Tissue Biopsy Cancer Detection Imaging Technology Tumor Marker Gene Expression

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DB Facade: A Web Cache with Improved data Freshness

DB Facade: A Web Cache with Improved Data Freshness

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International Symposium on Electronic Commerce and Security

作者： Xiongpai Qin Xiaoyun Zhou Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing China School of Information and Electrical Engineering China University of Mining and Technology Xuzhou Jiangsu China

Traditional Web database cache techniques have a major disadvantage, namely poor data freshness, because they employ an asynchronous data refresh strategy. A novel Web database cache, DB Facade, is proposed in this paper. DB Facade uses a main memory database to cache result sets of previous queries for subsequent reusing. Updates on backend database system are managed by delta tables, and then propagated to Web database cache in a near real-time manner, hence guarantee the freshness of data. DB Facade off loads query burden from backend database systems, and exploits the power of main memory database system to boost query performance. TPC-W testing result shows that the system's performance increases by about 17 percent.

关键词： database systems System testing Assembly systems Web pages Web server Electronic commerce data security Information security Laboratories data engineering

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The K-Step H Indices in Citation Networks at the Paper, Author, and Institution Levels

SSRN

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SSRN 2023年

作者： Yang, Alex Jie Wu, Linwei Zhang, Qi Wang, Hao Deng, Sanhong School of Information Management Nanjing University 22 Hankou Rd. Nanjing210093 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing210093 China International Joint Informatics Laboratory Nanjing University China

From the viewpoint of high-generation citation networks, h indices can be extended to global metrics at both basic and aggregated levels. To accomplish this, three types of networks are designed: the paper-paper network, the author-paper-paper network, and the institution-paper-paper network. The k-step h index is then proposed at the level of papers, authors, and institutions, respectively. Through a comprehensive empirical study based on the APS dataset, it is found that the k-step h index extends the depth and dimensionality of the Hirsh core, allowing for more global information. The consistency and convergent validity of the k-step h indices are quantitatively assessed. The results indicate that the k-step h index demonstrates a high degree of consistency and focuses on the potential for further research, and is capable of measuring the long-term reputation rather than short-term popularity. The convergent validity of the k-step h indices is rigorously tested using benchmark examples such as Nobel laureates and their publications, and they demonstrate superior performance in identifying seminal papers and prominent scientists compared to traditional metrics at the paper and author levels. The k-step h index also excels in ranking institutions, offering a promising new approach for evaluating the impact and influence of scientific entities at both the basic and aggregate levels. This opens up exciting avenues for future research. © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Performance study on logging to another main memory database

Performance study on logging to another main memory database

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International Conference on New Trends in Information and service Science, NISS

作者： Xiongpai Qin Xiaoyun Zhou Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing 100872 China Department of Computer Science and Technology Xuzhou Normal University Jiangsu 221008 China

In update intensive main memory database applications, huge volume of log records is generated, to maintain the ACID properties of the database system, the log records should be persistent efficiently. Delegating logging of one main memory database to another main memory database is proposed. The scheme is elaborated in detail in terms of architecture, logging & safeness levels, checkpointing, and recovery. Strict durability and relax durability are provided. When some form of non-volatile memory is used to temporarily holding log records, not only logging efficiency is improved, but also the scheme could guarantee full ACID of the system. We also propose using parallel logging to speedup log persistence by writing logs to multiple disks in parallel. Since interconnection network techniques progress by leaps and bounds, the scheme eliminates the concern about whether the system's overall performance may be slowed down by bandwidth and latency limitations. Experiment results demonstrate the feasibility of the proposal.

关键词： Checkpointing database systems Transaction databases Network servers Availability Nonvolatile memory Writing Communication industry Defense industry Wood industry

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Generative Aspect Based Sentiment Analysis for Online Health Community with data Augmentation

SSRN

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SSRN 2023年

作者： Han, Pu Ye, Dongyu Gu, Liang Chen, Wenqi Wei, Hongchen Li, Xiaoyan School of Management Nanjing University of Posts & Telecommunications Nanjing210003 China Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China School of Basic Medical Sciences Nanjing Medical University Nanjing210029 China

Accurate analysis of patients' feedback on various medical aspects is of great importance for improving the quality of healthcare services. In this paper, we address the task of extracting aspects and opinions by adopting a generative end-to-end deep learning model. And we address the challenge of limited high-quality labeled data in aspect-based sentiment analysis by introducing a data augmentation method. To evaluate the effectiveness of our proposed generative model and data augmentation technique in the healthcare domain, we collected reviews related to diagnosis and treatment from online health communities(OHC) and verified the effectiveness of the proposed model. The experimental results demonstrate the superiority of generative models in complex aspect-based sentiment analysis tasks. Furthermore, we find that our data augmentation method is effective in enhancing the experimental outcomes. Our work contributes to the advancement of natural language processing techniques in the healthcare domain, and it has the potential to improve the quality of healthcare services through more fine-grained analysis of patients' feedback. © 2023, The Authors. All rights reserved.

关键词： Sentiment analysis

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