9822006
Named Entity Recognition in Biomedical Literature Using Two-Layer Support Vector Machines
A beam receiver secured to an upper portion of a blade of an earth working equipment can rotate in a horizontal plane and move in a vertical direction and, accordingly, can catch a laser beam from a beam projector regardless of a direction of the equipment. When the beam has been deviated out of the beam receiver, the direction of the deviation is detected so that the beam can be received by the beam receiver again. The height of the beam receiver relative to the blade can be adjusted and the level of the blade can thereby be controlled very accurately.
36831968
Evaluating and Comparing Biomedical Term Identification Systems
In this paper, we propose a term identification system using conditional random fields (CRFs) on two biomedical datasets. Through employing several sets of experiments, we make a comprehensive investigation for different types of features. The final experimental results reflect that with carefully designed features i.e., adding not only the individual and dynamic features but also the combinational features, our system can identify biomedical terms with fairly high accuracy on both datasets, compared with other top systems already published in the literature.
13345001
Context-Sensitive Kernel Functions: A Distance Function Viewpoint
This paper extends the idea of weighted distance functions to kernels and support vector machines. Here, we focus on applications that rely on sliding a window over a sequence of string data. For this type of problems it is argued that a symbolic, context-based representation of the data should be preferred over a continuous, real format as this is a much more intuitive setting for working with (weighted) distance functions. It is shown how a weighted string distance can be decomposed and subsequently used in different kernel functions and how these kernel functions correspond to real kernels between the continuous, real representations of the symbolic, context-based representations of the vectors.
1280778
Splice Site Prediction using Support Vector Machines with Context-Sensitive Kernel Functions
This paper focuses on the use of support vector machines on a typical context-dependent classification task, splice site prediction. For this type of problems, it has been shown that a context-based approach should be preferred over a transfor- mation approach because the former approach can easily incorporate statistical mea- sures or directly plug sensitivity information into distance functions. In this paper, we designed three types of context-sensitive kernel functions: polynomial-based, radial basis function-based and negative distance-based kernels. From the experimental re- sults it becomes clear that the radial basis function-based kernel with information gain weighting gets the best accuracies and can always outperform their simple non-sensitive counterparts both in accuracy and in model complexity. And with well designed fea- tures and carefully chosen context sizes, our system can predict splice sites with fairly high accuracy, which can achieve the FP95% rate, 3.94 for donor sites and 5.98 for acceptor sites, an approximate state of the art performance for the moment.
35820562
Named Entity Recognition in Biomedical Literature: A Comparison of Support Vector Machines and Conditional Random Fields
In this paper, we propose two named entity recognition systems for biomedical literature, System1 using support vector machines and System2 using conditional random fields. Through employing several sets of experiments, we make a comprehensive comparison between these two systems. The final results reflect that System2 can achieve higher accuracy than System1, because System2 can catch more essential properties by handling the richer set of features, i.e., adding not only the individual and dynamic features as System1 does but also the combinational features, which can improve the performance further. Furthermore, with carefully designed features, System2 can recognize named entities in biomedical literature with fairly high accuracy, which can achieve the precision of 89.43%, recall of 83.32% and balanced F β= 1 score of 86.28%.
19596582
MMSE vector precoding with joint transmitter and receiver design for MIMO systems
The transmitter side (Tx) vector precoding (VP) shows excellent performance. However, joint transmitter and receiver (Tx-Rx) design might achieve further improvement. In this paper, we propose a novel joint Tx-Rx VP for multiple input multiple output (MIMO) systems. A unitary matrix is used at the receiver to partially equalize the channel. We design the joint Tx-Rx VP with the minimum mean square error (MMSE) criterion and deduce the general closed-form solution. Then we apply several methods including the singular value decomposition, QR decomposition and geometric mean decomposition (GMD) to specify the general joint Tx-Rx VP design. Moreover, by using the extended channel, we achieve an improved scheme to obtain further performance gain. Simulation results show that the specification with GMD method outperforms the other specifications and the Tx MMSE VP. The improved joint Tx-Rx MMSE VP with GMD is superior to other MMSE VP schemes.
32348366
Stabilization of switched linear systems with bounded disturbances and unobservable switchings
This paper studies the stabilization problem of switched linear systems with bounded disturbances. It is assumed that the system switches among an infinite set of uniformly controllable linear systems, and that the switching signals are not observable, but the switching duration has a lower bound. It will be shown that by combining on-line adaptive estimation and control in the controller design, a feedback control law can be constructed which makes the switched linear system globally stable.
4963124
Blind equalization Using ν- support vector regressor for constant modulus signals
The support vector machine has been recently developed for blind equalization of constant modulus signals. In this paper we propose to use a v-support vector regressor (nu-SVR) for blindly equalizing multipath channels because of the high generalization ability of the SVR for short burst sequences. A weighted least square procedure is presented for solving the blind nu-SVR equalizer. The performance of the proposed algorithm is analyzed by means of computer simulations.
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.
13519541
WS-SLA: A Framework for Web Services Oriented Service Level Agreements
Service level agreements (SLA) becomes the prevailing business model for delivery of a large number of products and services in telecommunication and IT arenas. We presents an integrated service level agreement model applied to operating supporting system (OSS), on the basis of WfMC workflow reference model and service oriented architecture (SOA). And an application scenario instance of SLA system architecture is described by a set of operations models by Business Process Execution Language (BPEL)