10172928
Texture-Consistent Shadow Removal
This paper presents an approach to shadow removal that preserves texture consistency between the original shadow and lit area. Illumination reduction in the shadow area not only darkens that area, but also changes the texture characteristics there. We achieve texture-consistent shadow removal by constructing a shadow-free and texture-consistent gradient field. First, we estimate an illumination change surface which causes the shadow and remove the gradients it induces. We approximate the illumination change surface with illumination change splines across the shadow boundary. We formulate estimating these splines as an optimization problem which balances the smoothness between the neighboring splines and their fitness to the image data. Second, we sample the shadow effect on the texture characteristics in the umbra and lit area near the shadow boundary, and remove it by transforming the gradients inside the shadow area to be compatible with the lit area. Experiments on photos from Flickr demonstrate the effectiveness of our method.
111120849
Generic Carrier-Based Core Model for Four-Terminal Double-Gate MOSFET Valid for Symmetric, Asymmetric, SOI, and Independent Gate Operation Modes
A generic carrier-based core model for undoped four-terminal double-gate (DG) MOSFET valid for symmetric, asymmetric, SOI, and independent gate operation modes is presented in this paper. Based on the exact solution of the 1-D Poisson's equation of a general DG-MOSFET configure, a generic drain current model is derived from Pao-Sah's double integral in terms of the carrier concentration. The model is verified by extensive comparisons with 2-D numerical simulations under different bias conditions to all four terminals. The concise mathematic formulation allows the unification various double-gate models into a carrier-based core model for compact DG-MOSFET model development.
953854
Efficient Schemes for Monte Carlo Markov Chain Algorithms in Global Illumination
Current MCMC algorithms are limited from achieving high rendering efficiency due to possibly high failure rates in caustics perturbations and stratified exploration of the image plane. In this paper we improve the MCMC approach significantly by introducing new lens perturbation and new path-generation methods. The new lens perturbation method simplifies the computation and control of caustics perturbation and can increase the perturbation success rate. The new path-generation methods aim to concentrate more computation on "high perceptual variance" regions and "hard-to-find-but-important" paths. We implement these schemes in the Population Monte Carlo Energy Redistribution framework to demonstrate the effectiveness of these improvements. In addition., we discuss how to add these new schemes into the Energy Redistribution Path Tracing and Metropolis Light Transport algorithms. Our results show that rendering efficiency is improved with these new schemes.
8081608
An analytic model for Ge/Si core/shell nanowire MOSFETs considering drift-diffusion and ballistic transport
In this paper an analytic model for Ge/Si core/shell nanowire MOSFETs (NWFETs) is developed. First, the electrostatic potential and charge model are derived out from classical device physics. Then the drift-diffusion drain current model is obtained and verified by comparisons with the numerical simulation. The ballistic current model is obtained with the approximately described quantummechanical effect through modifying the intrinsic carrier concentration under 2-dimensional confinement. With the proposed model, the performances of Ge/Si core/shell NWFETs are analyzed and significant characteristics are demonstrated in details. The analytic model in this paper provides a framework for further developing compact models of the NWFETs with Ge/Si core/shell heterostructure for circuit design and simulation.
29221183
Intelligent Crowd Simulation
Crowd simulation is a continuous challenge in computer animation. In this paper, we present an intelligent crowd simulation technique based on multiple autonomous agents. Each animated character (AC) is modeled as an autonomous agent, consisting of the perception, behavior planning and motion generation system. AC perceives the environment information, generates intentions and plans behaviors autonomously. To execute behaviors, appropriate motions are selected from the fundamental motion library (FML) and edited to create required motions. And the crowd behavior can be regarded as a combination of the individual behavior of each AC. The experiment shows the feasibility of this technique.
7524507
Video retargeting: automating pan and scan
When a video is displayed on a smaller display than originally intended, some of the information in the video is necessarily lost. In this paper, we introduce Video Retargeting that adapts video to better suit the target display, minimizing the important information lost. We define a framework that measures the preservation of the source material, and methods for estimating the important information in the video. Video retargeting crops each frame and scales it to fit the target display. An optimization process minimizes information loss by balancing the loss of detail due to scaling with the loss of content and composition due to cropping. The cropping window can be moved during a shot to introduce virtual pans and cuts, subject to constraints that ensure cinematic plausibility. We demonstrate results of adapting a variety of source videos to small display sizes.
7672380
Toward excitation and inhibition in neutrosophic logic: a multiagent model based on ying-yang philosophy
Logic should have been defined as the unity of contradiction between logic director and logic implementation. Chinese Daoism asserts that everything is defined in the unity of opposites, namely yin and yang, accordingly yang conducts change and yin brings it up (I-Ching, also known as Book of Changes). In this way logic is redefined in an indeterminate style to facilitate "both A and Anti-A" etc. in neutrosophics of logic. The unity of opposites is also described as neutrality in neutrosophy. An intermediate multi-referential model of excitation and inhibition is developed to derive a multiagent architecture of logic, based on Chinese yin-yang philosophy. This methodology of excitation/inhibition suggests a rhymed way of logic, leading to a dynamic methodology of weight strategy that links logic with neural network approach. It also confirms the crucial role of indeterminacy in logic as a fatal criticism to classical mathematics and current basis of science.
45720537
Bayesian Network Structure Ensemble Learning
Bayesian networks (BNs) have been widely used for learning model structures of a domain in the area of data mining and knowledge discovery. This paper incorporates ensemble learning into BN structure learning algorithms and presents a novel ensemble BN structure learning approach. Based on the Markov condition and the faithfulness condition of BN structure learning, our ensemble approach proposes a novel sample decomposition technique and a components integration technique. The experimental results reveal that our ensemble BN structure learning approach can achieve an improved result compared with individual BN structure learning approach in terms of accuracy.
856762
Research on System Integrative Evaluation Method Based on Survivability
Survivability is the essential ability of a system to fulfill its mission, in a timely manner, in the presence of attacks, failures, or accidents. Survivability should be considered beyond security for information system, and quantitative analysis can assess system survivability accurately for improvement. The paper presents a new type of analysis method for computer system survivability which considers both exterior environment and interior components and their correlations. The method can describe the survivability more precisely and exactly. The paper also elaborates on the process of using this method to evaluate system survivability and its advantages.
35354920
Color text image binarization based on binary texture analysis
In this paper, a novel binarization algorithm for color text images is presented. This algorithm effectively integrates color clustering and binary texture analysis, and is capable of handling situations with complex backgrounds. In this algorithm, dimensionality reduction and graph theoretical clustering are first employed. As the result, binary images related to clusters can be obtained. Binary texture analysis is then performed on each candidate binary image. Two kinds of effective texture features, run-length histogram and spatial-size distribution related respectively, are extracted and explored. Cooperating with an LDA classifier, the optimal candidate of the best binarization effect is obtained. Experiments with images collected from Internet has been carried out and compared with existing techniques, both show the effectiveness of the algorithm.
15290782
The Performance Analysis of an Improved Robust Beamforming Algorithm
The conventional minimum variance beamformer (MVB) is known to have better resolution and much better interference rejection capability when the array steering vector is accurately known. However, the major problem of the MVB is that it lacks robustness against the unknown array steering vector errors. Therefore, diagonal loading and its extended versions have been a popular approach to improve the robustness of MVB. In this paper, we provide an improved robust MVB (RMVB) algorithm, which has been derived by enforcing a spherical uncertainty set constraint on the array steering vector. The new algorithm has reasonable computation complexity and more numerical stability. Simulation results show that the new algorithm is effective in the presence of array steering vector errors.