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The rapidly increasing availability of healthcare data from multiple heterogeneous sources has spearheaded the adoption of data-driven approaches for improved clinical research, decision making, and patient management. The patient healthcare data are usually longitudinal and can be expressed as medical event sequences, where the events include clinical diagnosis, medications, laboratory reports, etc...
Failing to identify multi-word expression (MWE) may cause serious problems for many Natural Language Processing (NLP) tasks. Previous approaches heavily depend on language specific knowledge and pre-existing natural language processing (NLP) tools. However, many languages (including Chinese language) have less such resources and tools compared to English. An automatically learn effective features...
The data structure course is very important for information communication technology learning. However, some students can learn data structures well, but most students feel difficult to understand the contents of the data structure course. Therefore, a data structure exercise system applying self-regulated learning mechanism was used for students to learn by their own goals and strategies, and this...
We present a scheme to predict micro-scale weather based on region trajectories extracted from meteorological radar data. Moving regions representing micro-scale severe weather are extracted from radar data and form into trajectories, and based on the formed trajectories, we predict where the regions will move and its future scope by the approach of linear regression, which leads to prediction of...
With the rapid development of information technologies, which facilitates the perfection of healthcare systems, a variety of clinical data is becoming available. The patient Electronic Health Records (EHR) is one of important sources in healthcare data on which conducts personalized medicine. However, it is challenging if the raw EHRs are directly used to conduct related medical prediction due to...
Big data is now rapidly expanding into various domains such as banking, insurance and e-commerce. Data analysis and related studies have attracted more attentions. In health insurance, abuse of diagnosis is one of the key fraud problems, which damages the interests of insured people. To address this issue, numbers of studies have focused on this topic. This paper develops a healthcare fraud detection...
In the era of the mobile Internet, the problem of personal information leakage is becoming more and more serious. It is possible that third-parities (e.g., advertising companies, telecom operators) can easily obtain private user information by analyzing the Internet traffic flows to (or from) users. In this paper, in order to examine the degree of information leakage via the URLs, we propose an efficient...
The width of urban road is various. Roads with different width have different appearance in an image. Multi-resolution analysis-based method for road extraction was proposed. Firstly, some wide roads in IKONOS multi-spectral imagery were extracted through using level setbased method. While some narrow roads, which are non-salient in 4m multi-spectral imagery, were extracted from 1m fusion imagery...
Sequential data modeling has received growing interests due to its impact on real world problems. Sequential data is ubiquitous -- financial transactions, advertise conversions and disease evolution are examples of sequential data. A long-standing challenge in sequential data modeling is how to capture the strong hidden correlations among complex features in high volumes. The sparsity and skewness...
With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering...
According to the data feature of customer's consumption records of bank POS machine and the analysis depending on the actual requirements, a new modeling framework on consumption behavior of bank POS machines is presented in this paper, and further research on the implementation method of main aspects in the model is carried out. Firstly, we conduct data discretization and customer segmentation by...
With introduction of information granularity in decision systems in this paper, the importance of core attributes and information granularity is analyzed. Besides, an effective compound attribute measure is defined, which not only considers the measures of certain information in the positive region, but also considers the importance of information granularity beyond the positive region. Based on the...
The performance of many classifiers based on balanced data sets can't do well in imbalanced data sets. This article integrates the over-sampling method of Random-SMOTE (R-S), which is based on SMOTE method, in imbalanced data mining. We use the R-S method to increase the number of the minority randomly in the minority sample space until it is almost equal to the majority in data mining tasks. 5 UCI...
Rough sets theory can be used to research imprecise and incomplete problems in information systems. Conflict analysis and resolution play an important role in business, governmental, political and lawsuits disputes, labor-management negotiations, military operations and others. This article illustrates the proposed approach by means of a simple tutorial example of voting analysis in conflict situations...
The inhabited environments are MIMO, uncertainly, and nonlinear complex systems. This paper presents a novel intelligent fuzzy agent(IFA) based on input-output associational algorithm for intelligent inhabited environments. An input-output dynamic associational algorithm based on Hebb learning is proposed, which can divide a complex system into multiple simple systems and eliminate the irrelevant...
Recent years LiDAR data is widely used for constructing 3D terrain models which provide realistic impressions of the urban environment. This paper presents an automatic method for extracting 3D building model by the fusion of LiDAR data, 2D building outlines and orthoimage. 2D building outlines is generated by classifying the LiDAR data to terrain and off-terrain points, then detecting building edges...
For the popular DIV page layout in Web Pages, this paper presents a method based on the position of DIV to extract main text from the body of Web pages by reconstructing, remaining atomic DIV and analyzing DIV position. Experiments showed that the accuracy rate of extraction can reach more than 90%, with a high versatility and accuracy.
In the paper, support vector machine is presented to detection for vehicle' s overlap, which has stronger generalization ability than the algorithm based on the empirical risk, such as artificial neural network. In the process of detection for vehicle's overlap, principal component analysis is used to extract the features and reduce the dimension of features. Then, detection model for vehicle's overlap...
This paper investigates optimal reset law design of reset control systems with fixed reset time instants. Firstly, closed-loop reset control system is changed to discrete linear control system with reset values as control input. Then the optimal reset law design problems are transferred to standard linear quadratic regulation problems and the optimal reset laws are then obtained by solving some Riccati...
This paper propose a signature scheme based Trusted Computing Platform with two secret keys, while, using smarty card for enhancing the security of the system. For preventing from tampering with the information on public channel, the information and the signature will be encrypted with one-time padding system by the user and signatory. Finally, the article finishes correctness confirmation and security...
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