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Biologists synthesize research articles into coherent models—ideally, causal models, which predict how systems will respond to interventions. But it is challenging to derive causal models from articles alone, without primary data. To enable causal discovery using only literature, we built software for annotating empirical results in free text and computing valid explanations, expressed as causal graphs...
Bayesian optimization has been demonstrated as an effective methodology for the global optimization. However, it suffers from a computational bottleneck that the inference time grows cubically with the number of observations. In this paper, a Bayesian optimization based on the data-parallel approach is proposed to alleviate this problem. Firstly, an improved geometry motivated clustering algorithm...
Web Security Gateway (WSG) is a new type of network security product that maintains the security of trusted networks. In this paper, a WSG model for evaluating WSG performance is presented. This paper advances discussion of previous studies on series services under multiple service windows. The proposed model consists of a two-stage queuing system. The first stage is a network layer simulation. The...
Agent-based stochastic simulation is an established approach to study infectious diseases. Its advantage is the flexibility to incorporate important concepts. The effect of various mitigation strategies has been demonstrated using simulation models. Most of the previous studies compared a few options with a few selected scenarios. We propose to use genetic algorithms to search for the best vaccination...
Massive trust assessment (MTA) in an Online Social Network (OSN), i.e., computing the trustworthiness of all users in the network, is crucial in various OSN-related applications. Existing solutions are either too slow or inaccurate in addressing the MTA problem. We propose the OpinionWalk algorithm that accurately and efficiently conducts MTA in an OSN. OpinionWalk models trust by the Dirichlet distribution...
Exploring along the road of More Moore with integration degree increasing significantly, different wafer level 3-D technologies are developed facing various circumstances. Thermal issue has become an important concern in IC designing and manufacturing. Fan-out wafer level package (FOWLP), as one of the most popular packaging trends lately, compared to high cost through silicon via (TSV) based 3D integration...
Reservoir computing has been widely applied in dynamical system modeling and solving time-dependent problems at low computational expense. However, when confronting some complex tasks that exhibit multiple sets of dynamics, the conventional reservoir computing model with a single reservoir may become ineffective and powerless. Inspired by the modality-independent but functionally connected brain regions,...
Transparent computing is an implementation of ubiquitous computing that is aimed at providing active services for users. In transparent computing, the execution (computation) of computer instructions and data is temporally and spatially separated from their storage. Cloud computing solves the issue of data cloudlization, while transparent computing solves the one of software cloudlization. This paper...
In this paper, we address adaptive predictor feedback design for a simplified drilling system in the presence of disturbance and time-delay. The main objective is to stabilize the bottomhole pressure at a critical depth at a desired set-point directly. The stabilization of the dynamic system and the asymptotic tracking are demonstrated by the proposed adaptive control, where the adaptation employs...
Characterizing mobile traffic is important to network operators from a network performance and security standpoint. In many cases, such as a performance degradation or security threat, it is useful to know that traffic is being generated by a specific mobile application. Recent methods for identifying mobile traffic have relied on computationally expensive detailed inspection of HTTP flows which may...
In discriminative tracking algorithms, the accuracy of classifier which relies heavily on the selection of training samples can directly influence the performance of visual tracking. Motivated by above, a tracking algorithm is presented based on regularized approximate residual weighted subsampling in the paper. Through the subsampling procedure, the corrupted samples which exert adverse impacts on...
Measurement of the lexical properties of domain names enables many types of relatively fast, lightweight web mining analyses. These include unsupervised learning tasks such as automatic categorization and clustering of websites, as well as supervised learning tasks, such as classifying websites as malicious or benign. In this paper we explore whether these tasks can be better accomplished by identifying...
Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and...
An improved cloud resource revenue optimization models are proposed, which include the benefits of service providers and users negotiate SLA agreement. And the models define the constraint mechanism for describing service quality problems such as service response time and customer satisfaction. We design the comprehensive response indicator and use this indicator to quantify the rationality of the...
Thermal issue is becoming more and more serious when integrated circuits (IC) further explores along the road of More Moore with dramatic increments of integration degree and power density. Thermal management, including thermal design, modeling, and optimization, has been an important concern in the system-level design of 3D IC. Current thermal modeling for a system level 3D IC design usually relies...
Graph computing is widely utilized today, which severely requires the ability of processing graphs of billion vertices rapidly for social network analyzing, bio-informational network analyzing and semantic processing. Therefore, graph processing play a significant role in the research and application development. Data of music and movie recommendation and LDA topics can be modeled as bipartite graph...
Sky is one of the most significant subject matter commonly seen in outdoor photos. We propose a highly efficient sky detection algorithm. First, we detect a rough sky-ground boundary. Then, we calculate the parameters related to appearance of sky. Finally, we use these parameters to construct a hybrid probability model that indicates how possible a pixel belongs to sky. Moreover, an image processing...
Haze and mist always affect the quality of vision. If an image is suffered from haze or mist, then the object is unclear and the image seems whiter than the original one. There are several haze removal algorithms that can reduce the effect of haze and mist. However, if an image is not suffered from the haze and mist, applying the haze removal algorithm may darken the image. Therefore, in computer...
Infectious disease epidemics such as influenza and Ebola pose a serious threat to global public health. It is crucial to characterize the disease and the evolution of the ongoing epidemic efficiently and accurately. Computational epidemiology can model the disease progress and underlying contact network, but suffers from the lack of real-time and fine-grained surveillance data. Social media, on the...
Human action can be decomposed into a series of temporally correlated motions. Since the traditional bag-of-words framework based on local features cannot model global motion evolution of actions, models like Recurrent Neural Network (RNN) [15] and VideoDarwin [5] are accordingly explored to capture video-wise temporal information. Inspired by VideoDarwin, in this paper, we present a novel hierarchical...
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