International Journal of Advanced Science and Technology

8

Authors: Yu Zheng-tao, Deng Bin, Hou Bo, Han Lu and Guo Jian-yi

Word sense disambiguation has always been a key problem in Natural Language Processing. In the paper, we use the method of Information Gain to calculate the weight of different position's context, which affect to ambiguous words. And take this as the foundation. We select the ahead and back six position’s context of ambiguous words to construct the feature vectors. The feature vectors are endued with different value of weight in Bayesian Model. Thus, the Bayesian Model is improved. We use the sense of the HowNet to describe the meaning of ambiguous words. The average accuracy rate of the experiments of 10 Chinese ambiguous words was 95.72% in close test and the average accuracy rate was 85.71% in open test. The results showed that the method was proposed in this paper were very effective.

8

Authors: Jianhua Dai, Xiaochun Liu, Huaijian Zhang, Yu Yi, Jingjing Wang, Shaomin Zhang and Xiaoxiang Zheng

When recording extracellular neural activity, it is often necessary to distinguish action potentials arising from distinct cells near the electrode tip, a process commonly referred to as spike sorting or action potential sorting. Sorting of neuronal spikes plays a very important role in coding of neural information, which is a prerequisite for studying the brain function. In this paper, five major action potential classification methods including Template Matching, Wavelet Transform, Principal Component Analysis, Back-Propagation (BP) Neural Network, Two-stage Radius Basis Function Network are studied. Under the conditions of different levels of background noise, the performances of these methods are tested. This work may be helpful to choose classification method.

10

Authors: Giljong Yoo, and Eunseok Lee

This work concerns the development of a fault model of sensor for detecting and isolating sensor, actuator, and various faults in USNs (Ubiquitous Sensor Network). USN are developed to create relationships between humans, objects and computers in various fields. A management research of sensor nodes is very important because the ubiquitous sensor network has the numerous sensor nodes. However, Self-healing technologies are insufficient to restore when an error event occurs in a sensor node in a USN environment. A layered healing architecture for each node layer (3-tier) is needed, because most sensor devices have different capacities in USN. In this paper, we design a fault model and architecture of the sensor and sensor node separately for self-healing in USN. In order to evaluate our approach, we implement prototype of the USN fault management system to evaluate our approach. We compare the resource use of self-healing components in the general distributed computing(wired network) and the USN.

10

Authors: Sanghoon Kim, Sangmu Lee, Seungjong Kim and Joosock Lee

A mobile robot with various types of sensors via ubiquitous networks is introduced. We designed a mobile robot composed of TCP/IP network, wireless camera and several sensors in an environment, and show object avoiding and tracking methods necessary for providing diverse services desired by the people. To avoid obstacles(objects), active sensors such as infrared rays sensors and supersonic waves sensors are employed together and measures the range in real time between the obstacles and the robot. We focus on how to track a object well because it gives robots the ability of working for human. This paper suggests effective visual tracking system for moving objects with specified color and motion information. The proposed tracking system includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. Active contour information and shape energy function are used to exactly tract the objects with shape changes. Finally, real time mobile robot avoiding and tracking objects is implemented.

14

Authors: Rudy Adipranata, Eddy, Cherry G. Ballangan, and Ronald P. Ongkodjojo

Face segmentation has been used in many different applications, such as face tracking, video surveillance in security control system and human computer interface. In this paper we propose a two-stage face segmentation system that consists of face position detection and facial feature extraction. From the experimental results, the system produced a facial detection success rate of approximately 82.7 percent.