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By investigating the current situation of university library's digital and informational development, this paper analyzes the opportunities and challenges brought by cloud computing technology to the development of libraries. Two strategies of renting cloud services and building cloud platform are put forward to realize the cloud computing service of Digital Library in big data environment.
Activity recognition has become an important function in many emerging computer vision applications e.g. automatic video surveillance system, human-computer interaction application, and video recommendation system, etc. In this paper, we propose a novel semantics based group activity recognition scheme, namely SBGAR, which achieves higher accuracy and efficiency than existing group activity recognition...
Under the condition of supercooled large droplets (SLD), droplets breakup, splashing and bouncing should be considered. A droplet re-impingement model is applied to better study SLD impingement, and the Mcdonnell Douglas Aerospace (MDA) 3-element airfoils are simulated. Compared with normal model, impingement limits are minished slightly, local water collection efficiency decreases in some degree,...
With the continuous drive towards integrated circuits scaling, efficient performance modeling is becoming more crucial yet, more challenging. In this paper, we propose a novel method of hierarchical performance modeling based on Bayesian co-learning. We exploit the hierarchical structure of a circuit to establish a Bayesian framework where unlabeled data samples are generated to improve modeling accuracy...
We propose a shared protection scheme based on the sharing principle among multiple end-to-content backup paths in optical datacenter networks. Numerical results show it can reduce wavelengths consumption while ensuring the survivability against multi-failures.
Vehicular network is regarded as an important part of the Intelligent Transportation System (ITS). However, with the increasing number of vehicular applications, it is a challenge to meet the demands of both communication and computation. Fog computing can provide mobile users with the demanded services through low latency and short-distance local connections. This paper investigates the optimal deployment...
To satisfy the stringent requirement of ocean monitoring in Marine Intelligent Transportation System, Marine Sensor Networks (MSNs) is envisioned as one of the most effective solutions. In this paper, we study the Heterogeneous and Double Paths MSNs (HDPM) architecture with Sensors (SNs) in view of the reliability of the networks. And we propose a generic integer linear programming (ILP) model to...
Today's automotive industry is making a bold move to equip vehicles with intelligent driver assistance features. A modern automobile is now equipped with a powerful computing platform to run multiple machine learning algorithms for environment perception (e.g., pedestrian detection) and motion control (e.g., vehicle stabilization). These machine learning systems must be highly robust with extremely...
In this paper, we propose a novel Dual-Prior Bayesian Model Fusion (DP-BMF) algorithm for performance modeling. Different from the previous BMF methods which use only one source of prior knowledge, DP-BMF takes advantage of multiple sources of prior knowledge to fully exploit the available information and, hence, further reduce the modeling cost. Based on a graphical model, an efficient Bayesian inference...
With the aggressive scaling of integrated circuit technology, analog performance modeling is facing enormous challenges due to high-dimensional variation space and expensive transistor-level simulation. In this paper, we propose a kernel density based sparse regression algorithm (KDSR) to accurately fit analog performance models where the modeling error is not simply Gaussian due to strong nonlinearity...
In this article, we propose a new behavioral thermal modeling method for fast building performance analysis, which is critical for energy-efficient smart building control and management. The new approach is based on two recurrent neutral network architecture to obtain the compact nonlinear thermal models for complicated building. We start with a more realistic building simulation program, EnergyPlus,...
In order to determine the 3D motion of a point target from a monocular moving camera, a locating method is proposed by taking advantage of the property that the positions of the target in a short time are relative to each other and the kernel trick of least squares support vector machine (LS-SVM). This method has better noise immunity due to its robust estimation property, and has high accuracy as...
This paper presents the magnetic field modeling-based energy efficient routing for WSN which models the routing problem as a current-carrying solenoid and a free to turn magnet put into a uniform magnetic field respectively. The optimal routing is then performed through the path with the maximum generated magnetic field intensity for the solenoid technique and with minimum torque for the magnetic...
Efficient high-dimensional performance modeling of nanoscale analog and mixed signal (AMS) circuits is extremely challenging. In this paper, we propose a novel structure-aware modeling (SAM) technique. The key idea of SAM is to accurately solve the model coefficients by applying an efficient statistical algorithm to exploit the underlying structure of AMS circuits. As a result, SAM dramatically reduces...
This paper studies the optimal visibility coverage for autonomous robots in complex 3D environments. The perception sensor equipped on an inspection robot usually has a pyramid-shaped visible range with limited distance and angle. Finding the optimal pyramid visibility coverage for a given 3D region is NP hard; this paper presents an effective progressive integer linear programming algorithm to compute...
Efficient high-dimensional performance modeling of today's complex analog and mixed-signal (AMS) circuits with large-scale process variations is an important yet challenging task. In this paper, we propose a novel performance modeling algorithm that is referred to as Bayesian Model Fusion (BMF). Our key idea is to borrow the simulation data generated from an early stage (e.g., schematic level) to...
The paper presents nonlinear modeling study of belt conveyor system using the least square support vector machine (LS-SVM). Belt conveyor is a nonlinear, severe disturbance and time-varying system. So far, most of the existing models are based on mechanism laws, which are very useful for belt conveyor design. However, they are too complicated to be applied to control system design. To facilitate a...
A mobile ad hoc network (MANET) is a self-organized system comprised by multiple mobile wireless nodes. Due to the openness in network topology and the absence of centralized administration in management, MANET is vulnerable to attacks from malicious nodes. In order to reduce the hazards from these malicious nodes, we incorporate the concept of trust into the MANET, and build a subjective trust management...
Highway slope is an important part in the design and construction of highway. Especially in the complex geological condition area, road slope disasters occur frequently. So the stability of road slope is very essential to the safe traffic and the safety of human lives and their properties along the road. After the analysis of the existing methods of deformation measurement to physical model of highway...
In this paper, fractal theory and Diffusion limited aggregation (DLA) model of fractal growth were introduced. Growth rule, major properties of the model were presented and computer simulation of the model was performed on the platform of Visual C++ 6.0. Different simulation results were obtained with the change of the growth parameters. The effects of different growth parameters on fractal dimension...
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