A5100718286- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Data Management and Algorithms
- Advanced Database Systems and Queries
- Speech and Audio Processing
- Video Coding and Compression Technologies
- Advanced Image and Video Retrieval Techniques
- Advanced Computational Techniques and Applications
- Digital Marketing and Social Media
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
- Power Systems and Technologies
- Music and Audio Processing
- Neural dynamics and brain function
- Time Series Analysis and Forecasting
- Advanced Clustering Algorithms Research
- Privacy, Security, and Data Protection
- EEG and Brain-Computer Interfaces
- Impact of Technology on Adolescents
- Remote-Sensing Image Classification
- Misinformation and Its Impacts
- Image Retrieval and Classification Techniques
- Biometric Identification and Security
- Data Stream Mining Techniques
- Image and Signal Denoising Methods
University of Bristol
2025
Chinese University of Hong Kong, Shenzhen
2024
Huazhong University of Science and Technology
2013-2023
Shandong Jianzhu University
2021
Shandong Academy of Social Sciences
2021
Google (United States)
2020
Nanjing University
2005-2020
Union Hospital
2020
Nanjing Drum Tower Hospital
2020
Hebei University of Technology
2017-2019
Query optimizers rely on accurate cardinality estimates to produce good execution plans. Despite decades of research, existing estimators are inaccurate for complex queries, due making lossy modeling assumptions and not capturing inter-table correlations. In this work, we show that it is possible learn the correlations across all tables in a database without any independence assumptions. We present NeuroCard, join estimator builds single neural density over an entire database. Leveraging...
Cardinality estimation has long been grounded in statistical tools for density estimation. To capture the rich multivariate distributions of relational tables, we propose use a new type high-capacity model: deep autoregressive models. However, direct application these models leads to limited estimator that is prohibitively expensive evaluate range or wildcard predicates. produce truly usable estimator, develop Monte Carlo integration scheme on top can efficiently handle queries with dozens...
Rumor has drawn much of the attention researchers, considering its importance and influence, as well complexity. Under different circumstances, process results rumor spreading are also different. The method agent-based modeling is considered a good way to look into propagation. In this study, we put theme under circumstances online social networks like twitter, which from traditional network websites. Assuming that structure these websites kind scale free network, build specific model using...
The purpose of this study is to explore the changes in functional brain networks AD patients using complex network theory. In study, resting-state fMRI datasets 10 and 11 healthy controls were collected. Time series 90 regions extracted from after preprocessing. Pearson correlation method was used calculate coefficient between any two time series. Then, a wide threshold range selected transform adjacency matrix binary under different threshold. topology parameters each calculated, all them...
Recent years, the scale of spatial data is developing more and huge its storage has encountered a lot problems. Traditional DBMS can efficiently handle some big data. However, popular open source relational database systems are overwhelmed by high insertion rates, querying requirements terabytes that these handle. On other hand, key-value effectively support large operations. To resolve problems vector data's query, we bring forward HBase Spatial, scalable dada based on HBase. At first,...
We are motivated by the need for a generic object proposal generation algorithm which achieves good balance between detection recall, localization quality and computational efficiency. propose novel algorithm, BING++, inherits virtue of efficiency BING [1] but significantly improves its quality. At high level we formulate problem from probabilistic perspective, based on our BING++ manages to improve employing edges segments estimate boundaries update proposals sequentially. learning...
The COVID-19 pandemic demonstrated a pressing need for rapid, adaptive, and scalable manufacturing of vaccines reagents. With the transition into an endemic disease rising threats other emerging pandemics, production these biologicals requires stable sustainable supply chain accessible distribution methods. In this study, we demonstrate strength engineered filamentous fungal platform, Thermothelomyces heterothallica C1, high volumetric productivity full-length spike glycoprotein. Spike...
The security of private information users online is a critical topic, particularly since social networking applications became popular. According to Cutillo et al. [1], beyond the usual vulnerabilities that threaten any distributed application over Internet, networks raise specific privacy concerns due their inherent handling personal data.
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The existing opinion dynamics models mainly concentrate on the impact of opinions other and ignore effect social similarity between individuals. Social an individual their neighbors will also affect in real life. Therefore, evolution model considering (social-similarity-based HK model, SSHK for short) is introduced this paper. calculated using properties used to measure relationship By joint confidence bounds role neighbors’ selection changed significantly process opinions. Numerical results...
This paper addresses the need to deal with and control public opinion rumors. Existing strategies include degree, random, adaptive bridge strategies. In this paper, we use HK model present a strategy based on authority (PA). means utilizing influence of expert or high individuals whose opinions obtain optimum effect in shortest time possible thus reach consensus opinion. Public (PA) is only influenced by individuals' attributes (age, economic status, education level) not their degree...
Monarch is a globally-distributed in-memory time series database system in Google. runs as multi-tenant service and used mostly to monitor the availability, correctness, performance, load, other aspects of billion-user-scale applications systems at Every second, ingests terabytes data into memory serves millions queries. has regionalized architecture for reliability scalability, global query configuration planes that integrate regions unified system. On top its distributed architecture,...
Social acquaintance networks influenced by social culture and policy have a great impact on public opinion evolution in daily life. Based the differences between socio-culture policy, three different (kinship-priority network, independence-priority hybrid network) incorporating heredity proportion ph variation pv are proposed this paper. Numerical experiments conducted to investigate network topology phenomena during evolution, using Deffuant model. We found that kinship-priority networks,...
Two distinct cognitive styles exist from the perspective of cognition: field‐dependence and field‐independence. In most public opinion dynamics models, people only consider that individuals update their opinions through interactions with other individuals. This represents field‐dependent style individual. The field‐independent is ignored in such cases. We both propose a evolution model based on (CS model). neighbors experiences individual represent cognition cognition, respectively, combines...
The conventional mathematical models that are used for traffic distribution and mode choice forecasts consider neither the individual heterogeneity on micro level nor changeable scenes. This prompted us to propose a new forecast method composed of survey, an artificial transportation system (ATS), computational experiments. We introduced BDI modeling in agent-based ATS. considers individual's psychological characteristics combination with logical thinking, which was passenger agents, deduce...