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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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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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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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Amplitudes and frequencies cross modulation of epileptic EEG between 16 leads 3

Amplitudes and frequencies cross modulation of epileptic EEG...

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3rd International Conference on Biological Information and Biomedical engineering, BIBE 2019

作者： Cai, Yujie Dai, Jiafei Li, Jin Wang, Jun Hou, Fengzhen Smart Health Big Data Analysis and Location Services Engineering Lab Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Nanjing General Hospital of Nanjing Military Command Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi'an China Key Laboratory of Biomedical Functional Materials China Pharmaceutical University Nanjing China

ISBN: (纸本)9783800750269

Epilepsy is caused by abnormal brain nerves. In order to analyze the similarities and differences of EEG signals between patients with epilepsy and normal people, this paper introduced a cross modulation algorithm. This paper analyzed the correlation between amplitude and frequency between EEG signals in various parts of the brain. The approach overcomes the limitation to complexity of the algorithm and found abnormalities in EEG signals of temporal lobe and occipital lobe. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Computational complexity

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Cross-Modulated Amplitudes and Frequencies of Epileptic EEG 4

Cross-Modulated Amplitudes and Frequencies of Epileptic EEG

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2019 4th Annual International Conference on Information System and Artificial Intelligence, ISAI 2019

作者： Cai, Yujie Dai, Jiafei Li, Jin Wang, Jun Hou, Fengzhen Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing210003 China Nanjing General Hospital of Nanjing Military Command Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi'an China Key Laboratory of Biomedical Functional Materials China Pharmaceutical University Nanjing China

Epilepsy is a neural disorder with the hallmark of recurrent seizures. To characterize the epileptic brain electrical activities, we employed the cross modulation of instantaneous amplitudes and frequencies to separate synchronous and anti-synchronous modulation. Amplitude-amplitude, amplitude-frequency and frequency-frequency cross modulation were adopted to analyse the difference between EEG signal of epileptic patients and that of normal people. By comparing the observed patterns with two groups of EEG signals we demonstrate that the cross-modulation exponentials at the temporal region and the occipital region of right hemisphere are significant different. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Frequency modulation

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Salient Patch Based NAS for Grading of Colorectal Cancer Histology Images 13

Salient Patch Based NAS for Grading of Colorectal Cancer His...

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13th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2022

作者： Meng, Hang Li, Fei Yang, Zhen Zhu, Qiang Fan, Chaogang Zhan, Shu Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Anhui Province Hefei230009 China The Second Affiliated Hospital of Anhui Medical University Anhui Province Hefei230601 China Tongcheng Teachers College Anhui Province Tongcheng231400 China Department of General Surgery The Affiliated BenQ Hospital of Nanjing Medical University Jiangsu Province Nanjing210021 China

ISBN: (纸本)9781950492619

Digital histopathological tissue images are gold material for cancer diagnosis and grades. Convolutional Neural Networks (CNNs) are state-of-the-art models in many image classification tasks. However, considering the limited computing resources, it is not practical to directly train CNNs on gigapixel resolution histopathological tissue images. Therefore, the entire histopathological image is commonly divided into a grid of patches and then fed each patch to CNNs, but not all patches are necessary for specific tasks. Besides, although CNNs are excellent image classifiers, many pre-trained models are based on natural images. Neural Architecture Search (NAS) can realize automatic search, construction, and training specific problemoriented networks. We present salient patch based NAS for grading colorectal cancer (CRC) histology images with these motivations. The proposed framework first applies the classic classification network to extract significant patches from the whole image, then use the network obtained by NAS to grade the patches, and finally aggregates the patch-level predictions to generate the entire CRC histological image label. Our experiments on microscopic colorectal tissue images demonstrate that the proposed method is sufficient to obtain more accurate classification results compared to its counterparts. We also conducted a comprehensive analysis of the different scenarios of the proposed method. © by the International Institute of Informatics and Systemics.

关键词： Grading

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SAMPLING LOVÁSZ LOCAL LEMMA FOR GENERAL CONSTRAINT SATISFACTION SOLUTIONS IN NEAR-LINEAR TIME

arXiv

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arXiv 2022年

作者： He, Kun Wang, Chunyang Yin, Yitong The Key Lab of Data Engineering and Knowledge Engineering MOE Renmin University of China No. 59 Zhongguancun Street Haidian District Beijing China State Key Laboratory for Novel Software Technology Nanjing University 163 Xianlin Avenue Jiangsu Province Nanjing China

We give a fast algorithm for sampling uniform solutions of general constraint satisfaction problems (CSPs) in a local lemma regime. Suppose that the CSP has n variables with domain size at most q, each constraint contains at most k variables, shares variables with at most Δ constraints, and is violated with probability at most p by a uniform random assignment. The algorithm returns an almost uniform satisfying assignment in expected poly(q,k, Δ) ·(n) time, as long as a local lemma condition is satisfied: k · p · q2 · Δ5 ≤ C0 for a suitably small absolute constant C0. Previously, under similar local lemma conditions, sampling algorithms with running time polynomial in both nand Δ were only known for the almost atomic case, where each constraint is violated by a small number of forbidden local configurations. The key term Δ5 in our local lemma condition also improves the previously best known Δ7 for general CSPs [JPV21b] and Δ5.714 for atomic CSPs, including the special case of k-CNF [JPV21a, HSW21]. Our sampling approach departs from previous fast algorithms for sampling LLL, which were based on Markov chains. A crucial step of our algorithm is a recursive marginal sampler that is of independent interests. Within a local lemma regime, this marginal sampler can draw a random value for a variable according to its marginal distribution, at a cost independent of the size of the CSP. Copyright © 2022, The Authors. All rights reserved.

关键词： Constraint satisfaction problems

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Epileptic brain network analysis based on Kendall's improved synchronization algorithm 1

Epileptic brain network analysis based on Kendall's improved...

引用

1st International Conference on Physics, Mathematics and Statistics, ICPMS 2018

作者： Ding, Chuchu Sun, Ting Zou, Xin Dai, Jiafei Li, Jin Wang, Jun Hou, Fengzhen Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Nanjing General Hospital of Nanjing Military Command Nanjing210002 China College of Physics and Information Technology Shaanxi Normal University Xi'an China Key Laboratory of Biomedical Functional Materials China Pharmaceutical University Nanjing210009 China

In this paper, we use a new algorithm, the IRC algorithm, to improve the Kendall algorithm. Research on complex networks has gradually deepened into all areas of social science. The study of brain networks has become a hot topic in the study of brain function. The method of wavelet filtering is used to filter the EEG data to obtain the required α-band (8-16 Hz). Using the improved IRC algorithm, the brain functional network is constructed based on the EEG data, and the related characteristics of the brain network constructed are analyzed. The experimental results show that the method is suitable for distinguishing the network degree indicators of epilepsy and normal brain tissue, and further deepening the study of the neurokinetic behavior of the brain. © Published under licence by IOP Publishing Ltd.

关键词： Complex networks

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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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Gestational Diabetes Mellitus Prediction Based on Two Classification Algorithms 12

Gestational Diabetes Mellitus Prediction Based on Two Classi...

引用

12th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2019

作者： Zhong, Weiyang Jiang, Shanxi Wu, Wei Peng, Danhong Xu, Tian Wang, Jun Wang, Gongdao Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China China Tower Corporation Limited Nantong Branch China Key Laboratory of Environment Medicine and Engineering Ministry of Education School of Public Health Southeast University Nanjing210009 China Department of Obstetrics and Gynecology Zhongda Hospital Southeast University Nanjing School of Science China Pharmaceutical University Nanjing China

ISBN: (纸本)9781728148526

Gestational diabetes mellitus (GDM) is a disease with normal glucose tolerance before pregnancy and only diabetes during pregnancy. The discovery of GDM has a long history. The specific causes and mechanisms of its occurrence are still unclear. There is a lack of research on intelligent diagnosis of GDM. GDM has many adverse effects on pregnant women and fetuses, which is of great significance for the early diagnosis of GDM. Based on the measured data of the hospital, this paper realizes the intelligent diagnosis of GDM by using a improved KNN algorithm and a improved BP neural network. © 2019 IEEE.

关键词： Genetic algorithms

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