Web applications under attack may perform undesirable behaviors against their use case specification. These attacks exploit web vulnerabilities which are usually considered as consequences of abusing web *** paper pro...
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Web applications under attack may perform undesirable behaviors against their use case specification. These attacks exploit web vulnerabilities which are usually considered as consequences of abusing web *** paper proposes a resource-based approach to formalize use case specification for web *** goal of the research is to identify and organize web resources,and to integrate web resources into use cases in a structured way. First,we filter web resource information based on the lexical analysis of the original use case ***,we identify hidden web resources that are not listed in the event flow but required during the realization of the *** that,we organize these web resources into a web resource ***,the formalized use case specification is constructed into a tree structure along with a defined event flow *** resource-based use case specification enables security analysts to analyze the web vulnerabilities in terms of the resources required by each *** is helpful to elicit security requirements.
In the task of product image search, the database consists of clean versions of product images, while the query photos are often captured from mobile phone cameras under uncontrolled conditions. Conventional methods u...
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In the task of product image search, the database consists of clean versions of product images, while the query photos are often captured from mobile phone cameras under uncontrolled conditions. Conventional methods usually adopt the SIFT based bag-of-words(BoW) representation of the whole query image, which suffers from the interference of background noise. To address the problem, we extract multiple candidate regions from the query image and compute the regional similarity to database images individually. Then a verification strategy is proposed to evaluate the similarity based on regional semantic evidences. With the proposed method, we can not only improve the search accuracy, but also obtain the location of the product in the query image. Extensive experiments on two public datasets demonstrate the effectiveness of our method.
The ever-growing spatial and spectral resolution of hyperspectral imagery has increased interest in dimensionality reduction that takes place on-board the data-acquisition ***, traditional dimensionality-reduction alg...
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The ever-growing spatial and spectral resolution of hyperspectral imagery has increased interest in dimensionality reduction that takes place on-board the data-acquisition ***, traditional dimensionality-reduction algorithms are data dependent,computationally expensive, and, consequently, prohibitive for many resource-constrained airborne or satellite-borne sensor platforms. Random projections offer a means for accomplishing dimensionality reduction simultaneously with data acquisition, such that the sensor projects onto a lower-dimensional subspace chosen at random. The problem of reconstruction from random projections is addressed, considering both compressed sensing as well as an alternative based on principal components. The effect of random projections on the performance of hyperspectral analysis is also investigated, with particular focus on anomaly detection and classification. It is observed that strongly anomalous vectors are likely to be identifiable in the domain of the random projections even at low dimension, while widely separated classes are likely to remain so. Finally, the ability of applying such anomaly or class analysis in the random-projection domain is exploited to improve subsequent reconstruction of the hyperspectral dataset.
To obtain and maintain user models are very important for personalized service *** quality of personalized services directly relies on the quality of the user *** surprisingly,many web sites have adopted different way...
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To obtain and maintain user models are very important for personalized service *** quality of personalized services directly relies on the quality of the user *** surprisingly,many web sites have adopted different ways to construct user models so that they can recommend goods or services to individuals according to user's preference. Obviously,to integrate separate user models coming from different sources for one user can provide more comprehensive and accurate user *** there exist the requirements to obtain integrated user models by sharing their user models. After discussing the requirements of sharing user models,an open user model service platform is ***'s architecture, key technologies and an implemented prototype are introduced.
Time series clustering has been applied in many scientific domains and has attracted much attention in recent years. In this paper, a novel hypergraph based clustering method for time series is proposed, combining mul...
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Time series clustering has been applied in many scientific domains and has attracted much attention in recent years. In this paper, a novel hypergraph based clustering method for time series is proposed, combining multiple similarity measures and hypergraph partitioning. We firstly build the hypergraph for time series dataset using multiple similarity measures, where each time series is represented by vertex and hyperedge is formed based on the similarity relation among time series. Then, the vertices in the constructed hypergraph are grouped by the hypergraph partitioning method to identify the clusters of time series. Two different strategies for hypergraph construction are presented in detail, resulting in two specific methods. Empirical experiments of time series clustering with the UCR archive are conducted for the purpose of evaluation. The results demonstrate that the proposed methods outperform contrast clustering methods in most of the tested datasets and also achieve better performance than the network based methods under consideration, owe to the combination of advantages of hypergraph and various similarity measures.
Rule engine has become an indispensable component for many clinical decision support systems. Due to the complexity and heterogeneity of clinical data, one big challenge for rule-based clinical applications is mapping...
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Rule engine has become an indispensable component for many clinical decision support systems. Due to the complexity and heterogeneity of clinical data, one big challenge for rule-based clinical applications is mapping the data from various data sources to rule variables. This paper proposed a rule engine integration profile that uses a shared ontology between the rule engine and external systems to facilitate data acquisition. Based on the integration profile, a diagnostic clinical decision support application was successfully deployed in a Chinese hospital.
Linear discriminant analysis has gained extensive applications in supervised classification and dimension reduction. In LDA formulation,original patterns with high dimension can be projected to lower dimension through...
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Linear discriminant analysis has gained extensive applications in supervised classification and dimension reduction. In LDA formulation,original patterns with high dimension can be projected to lower dimension through a transfer matrix which is fundamental to clustering,nearest neighbor searches,and *** transfer matrix is usually viewed as a distance metric. However,the classification accuracy under the LDA metric is neither optimal nor suboptimal because physical datasets often appear multimodal *** paper proposes a penalized scheme for LDA to improve the classification rate by using the information of misclassified *** method is evaluated to be robust and effective by a great number of datasets from the machine learning repository.
For low permeability bottom water reservoir fracturing, it is easy that hydraulic fracture penetrate into aquifer zones and lead to problematic production of water when potentially productive zones are located a few m...
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For low permeability bottom water reservoir fracturing, it is easy that hydraulic fracture penetrate into aquifer zones and lead to problematic production of water when potentially productive zones are located a few meters above water or the interlaminar stress contrast is not big enough. Swellable particle plugging agent as a new profile control agent has been applied widely and achieved good results. In order to ensure the performance of bottom water fracturing with swellable agent, the shut-off capacity and intensity on pore has been tested by physical model experiments and a new mathematic model for artificial barrier has been proposed. It can provide some reference on reasonable application of swellable plugging agent in bottom water reservoir fracturing. The application results in Luliang oilfield show that swellable plugging agent can effectively seal water layer and achieved a significant increase of oil production.
Influenced by the noises,for example,eyelid and eyelash occlusions,iris localization algorithms are difficult to keep a right balance between real-time quality and accuracy. Therefore,a novel iris localization method ...
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Influenced by the noises,for example,eyelid and eyelash occlusions,iris localization algorithms are difficult to keep a right balance between real-time quality and accuracy. Therefore,a novel iris localization method with effective noise eliminating is proposed in this *** the iris' inner edge location,morphological open is used to eliminate noise based on separating pupil region by *** the pupil's center and radius are located accurately by gray *** the iris' outer edge location,morphological close is proposed to eliminate the rich texture within the iris *** on this method,an edge detection template to search four directional points within a small scope of the probable boundary is designed and thus the iris's centre and radius can be *** results show that,compared with the pre-algorithms,the new algorithm not only greatly improves the accuracy and the speed, but also shows good robustness.
The emphasis is on the key-frame extraction technique in content-based video *** with problems existed in the traditional clustering algorithms,an improved shots keyframe extraction algorithm based on fuzzy C-means cl...
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The emphasis is on the key-frame extraction technique in content-based video *** with problems existed in the traditional clustering algorithms,an improved shots keyframe extraction algorithm based on fuzzy C-means clustering is *** the color feature information in the video frames,and then through the improvement of the clustering algorithm of video sequences to acquire the center value of various classes and the membership degree of every frame relative to the classes,finally the shots will be clustered into several *** to the relatively uniform of the contents in the sub-shots and the large differences between different classes,as well as the value of the maximum image entropy corresponds to the maximum amount of information in the information theory,the value of maximum entropy frame is extracted as the key-frame from each *** method overcomes the shortcomings of the traditional key-frame extraction methods that the numbers of the key-frame are fixed. Experiments based on various video sequences show that the algorithm is more reasonable.
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