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We constructed a new secure searchable encryption scheme aided by a computationally powerful but untrusted cloud server. Our scheme allows a client to provide a single search token to the server, but still allows the server to search for that token's word over all the documents he can access that encrypted with different keys. We achieved the scheme using multikey fully homomorphic encryption (MFHE)...
E-commerce has become a vital contributor to China's national economy. A mass of users' behavioral data on E-commerce platforms such as browse, click and purchase have being accumulated during DT era. Using machine learning algorithms to explore patterns behind big data grows into a new focus of research. In this paper, firstly, we use SQL Server to do feature extraction on those behavioral data....
In this paper, we develop a RRAM compact model accounting for random telegraph noise (RTN) effect. In particular, we develop a Monte Carlo method to effectively capture the behaviors of the traps in the tunneling gap, which can be used to predict the current fluctuation caused by RTN. The model is validated with experimental data under various operating conditions. The model can be applied to study...
The applications hosted in a datacenter share more than just servers; they also share electrical circuits. Datacenter managers provision the power capacity of these circuits to hosted applications, often based on their peak power needs. In this work, we studied the actual and peak power needs of 3 real datacenters, using data from 1) hardware manufacturers and 2) actual, observed power needs to estimate...
The missing data classification problem is one of the common problems in machine learning. Conventional method eliminates the samples with missing values. In this paper, matrix completion, as a new method is proposed for filling the missing data. And this method and two traditional methods, eliminating the samples with missing values and filling the missing data based on the sample similarity, are...
Some statistical and machine learning methods have been proposed to build hard drive prediction models based on the SMART attributes, and have achieved good prediction performance. However, these models were not evaluated in the way as they are used in real-world data centers. Moreover, the hard drives deteriorate gradually, but these models can not describe this gradual change precisely. This paper...
Environmental factor, as an important parameter in reliability assessment, has been an important issue in the reliability engineering research. The definition of environmental factor for success-failure type data is the unreliability ratio of products between two different environments. When the experimental data obtained were zero-failure data, the value of denominator would be zero when using the...
This paper investigated the application of Bayes' theorem in life distribution. The uncertainty of the model itself was rarely cared about Bayesian theory. So probability distribution model uncertainty and structural parameter uncertainty was researched through Bayes' theorem. This paper developed the fatigue life distribution mode of turbine blade. Firstly, find the best model by quantification of...
Remaining useful life (RUL) is important to manage life circles of machineries and reduce maintenance cost. Support vector machine (SVM) is a promising algorithm for RUL prediction because of its advantages to deal with small size of training sets and multi-dimensional data. Recently, many methods of RUL prediction using SVM have been proposed. In this paper, a review over 60 references within the...
Roof segmentation, i.e. separating building roofs, is a key step in deriving building models as it directly influences the precision and accuracy of the final building models. Even though various segmentation methods have been proposed, convincing and completing evaluations of the segmentation results are rarely discussed. This paper proposes several approaches to provide quantitative evaluation of...
With the popularity of Internet of Things, the next logical step will focus on the application layer on top of network connectivity, especially Web of Things. While most of the existing efforts on Web of Things are focused on device mash up and data collection, in this paper a semantic web of things framework is proposed to leverage Semantic Web as the unified mechanism for monitoring, tasking, presentation,...
Cipher text-Policy Attribute Based Encryption (CP-ABE) is a promising cryptographic primitive for fine-grained access control of shared data. However, when CP-ABE is used to control outsourced data sharing, it confronts two obstacles. Firstly, the data owner must trust the attributes authority, secondly, the issue of attribute revocation of CP-ABE schemes, which suffers from such problems as different...
The vergence-accommodation conflict, excessive screen disparity, binocular distortions and the motion component in stereoscopic videos are considered as main factors that may induce visual discomfort. In our previous study which was based on the experts-only experiment, we also found that the large relative disparity between the foreground and background and the fast planar motion were more likely...
Cross-lingual projection encounters two major challenges, the noise from word-alignment error and the syntactic divergences between two languages. To solve these two problems, a semi-supervised learning framework of cross-lingual projection is proposed to get better annotations using parallel data. Moreover, a projection model is introduced to model the projection process of labeling from the resource-rich...
Due to complexity, multiplicity and randomness of table tennis matches, it is necessary to develop some skill and tactic diagnostic models especially an efficient scoring model to get some skill and tactics data for table tennis matches. A scoring model is developed for table tennis matches based on video image processing technology. An input match video is used to analysis the skill and tactic of...
This paper presents results from an investigation of global wave energy resources derived from analysis of ECMWF ERA-40 wave re-analysis data spanning the 45 year period from September 1957 to August 2002. The global distribution of wind sea energy and swell energy, based on the wave spectra partition, are presented for the first time. The spatial and temporal variations of the global wave energy,...
The widely used geospatial web services technology has provided a new means for geospatial data interoperability. Web Map Service (WMS) is a standardized geospatial web service from the Open Geospatial Consortium (OGC). WMSs can be used for requesting and producing maps on the Internet, and have been widely adopted in the Geographic Information System (GIS) community. These WMSs make remote sensing...
Quality of Service (QoS) has been widely used to support dynamic Web Service (WS) selection and composition. Due to the volatile nature of QoS parameters, QoS prediction has been put forward to understand the trend of QoS data volatility and estimate QoS values in dynamic environments. In order to provide adaptive and effective QoS prediction, we propose a WS QoS prediction approach, named WS-QoSP,...
Simulation modeling is an increasingly popular and effective tool for analyzing transportation problems that are not amendable to study by other means. For any simulation study, model calibration and validation is a crucial step to obtaining any results from analysis. This paper proposed a systematic, practical procedure for microscopic simulation model calibration and validation. The validity of...
In order to meet the educating and training requirements of tactical communication network (TCN), one advanced means is to develop its simulative training system. Firstly, the general framework of TCN simulative training system was designed, which included the system constitution, software structure and application manner. Secondly, a single federation and multi federation architecture were proposed,...
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