Relevance feedback based on SVM classifier shows a good performance recently but the finite feedback counts limited by user's patience and the small sample size problem are not solved well, Co-SVM does a good job ...
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In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density λ ∈ [1, n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficien...
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Web workloads are known to vary dynamically with time which poses a challenge to resource allocation among the applications. In this paper, we argue that the existing dynamic resource allocation based on resource util...
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Web workloads are known to vary dynamically with time which poses a challenge to resource allocation among the applications. In this paper, we argue that the existing dynamic resource allocation based on resource utilization has some drawbacks in virtualized servers. Dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines real time measurements and analysis of user experience for resource allocation. We evaluate our proposal using Webbench. The experiment results show that these techniques can judiciously allocate system resources.
Regularized Low-rank approximation with missing data is an effective approach for Collaborative Filtering since it generates high quality rating predictions for recommender systems. Alternative LS (ALS) method is one ...
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Digital watermarking is an efficient method to protect multimedia documents. Robust watermarks, which survive to any change or alteration of the protected documents, are typically used for copyright protection. Fragil...
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MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelle...
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ISBN:
(纸本)9781457716669
MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context). The microarray gene expression profile of brain tumors from 356 patients (The Cancer Genome Atlas dataset) was converted into a CoMi activity pattern, and showed significant positive correlation with the corresponding miRNA expression pattern. In a breast cancer cohort, the differential CoMi activity between good prognosis (longer survival) vs. bad prognosis patients forms a scale-free network, which highlighted a group of important cancer-related microRNAs and GO terms, e.g. hsa-miR-34a and 'cell adhesion'. Then two breast cancer cohorts were used in outcome prediction in an independent test. Using a popular T-test feature selection method and a support vector machine (SVM) classifier with 10-fold cross-validation, the CoMi activity feature achieves an area under curve (AUC) of 0.7155, better than the AUC value of 0.6339 for feature selection based on mRNA expression. In an independent test, CoMi feature selection achieved an AUC of 0.6874. Survival analysis also shows signatures defined by CoMi activity was predictive of survival and superior to mRNAs signatures. In short, we have demonstrated the first interrogation of dynamic remodeling of context specific miRNAs regulation networks in cancer. The altered microRNAs regulation on specific contexts could be used to predi
ISS (Instruction Set Simulator) plays an important role in pre-silicon software development for ASIP. However, the speed of traditional simulation is too slow to effectively support full-scale software development. In...
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ISS (Instruction Set Simulator) plays an important role in pre-silicon software development for ASIP. However, the speed of traditional simulation is too slow to effectively support full-scale software development. In this paper, we propose a hybrid simulation framework which further improves the previous simulation methods by aggressively utilizing the host machine resources. The utilization is achieved by categorizing instructions of ASIP application into two types, namely custom and basic instructions, via binary instrumentation. Then in a way of hybrid simulation, only custom instructions are simulated on the ISS and basic instructions are executed fast and natively on the host machine. We implement this framework for an industrial ASIP to validate our approach. Experimental results show that when the implemented ISS, namely GS-Sim, is applied to practical multimedia decoders, an average simulation speed up to 1058.5MIPS can be achieved, which is 34.7 times of the state-of-art dynamic binary translation simulator and is the fastest to the best of our knowledge.
Sink Scheduling, in the form of scheduling multiple sinks among sink sites to leverage traffic burden, is an effective mechanism for the energy-efficiency of wireless sensor networks (WSNs). Due to the inherent diffic...
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This paper introduces a two-stage Linear Logic based program synthesis approach to automatic RESTful web service composition. The Linear Logic theorem proof is applied at both resource and service invocation method le...
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