206793088
A fuzzy ontology and its application to news summarization
In this paper, a fuzzy ontology and its application to news summarization are presented. The fuzzy ontology with fuzzy concepts is an extension of the domain ontology with crisp concepts. It is more suitable to describe the domain knowledge than domain ontology for solving the uncertainty reasoning problems. First, the domain ontology with various events of news is predefined by domain experts. The document preprocessing mechanism will generate the meaningful terms based on the news corpus and the Chinese news dictionary defined by the domain expert. Then, the meaningful terms will be classified according to the events of the news by the term classifier. The fuzzy inference mechanism will generate the membership degrees for each fuzzy concept of the fuzzy ontology. Every fuzzy concept has a set of membership degrees associated with various events of the domain ontology. In addition, a news agent based on the fuzzy ontology is also developed for news summarization. The news agent contains five modules, including a retrieval agent, a document preprocessing mechanism, a sentence path extractor, a sentence generator, and a sentence filter to perform news summarization. Furthermore, we construct an experimental website to test the proposed approach. The experimental results show that the news agent based on the fuzzy ontology can effectively operate for news summarization.
17825977
Ontology-based fuzzy event extraction agent for Chinese e-news summarization
Abstract An Ontology-based Fuzzy Event Extraction (OFEE) agent for Chinese e-news summarization is proposed in this article. The OFEE agent contains Retrieval Agent (RA), Document Processing Agent (DPA) and Fuzzy Inference Agent (FIA) to perform the event extraction for Chinese e-news summarization. First, RA automatically retrieves Internet e-news periodically, stores them into the e-news repository, and sends them to DPA for document processing. Then, the DPA will utilize the Chinese Part-of-speech (POS) tagger provided by Chinese knowledge information processing group to process the retrieved e-news and filter the Chinese term set by Chinese term filter. Next, the FIA and Event Ontology Filter (EOF) extract the e-news event ontology based on the Chinese term set and domain ontology. Finally, the Summarization Agent (SA) will summarize the e-news by the extracted-event ontology. By the simulation, the proposed method can summarize the Chinese weather e-news effectively.
20301861
Ontology-based intelligent healthcare agent and its application to respiratory waveform recognition
In recent years, the population has been aging gradually, and the number of patients with chronic respiratory disease has grown increasingly; therefore the respiratory healthcare plays an important role in the clinical care. This paper presents an ontology-based intelligent healthcare agent for the respiratory waveform recognition to assist the medical staff in judging the meaning of the graph reading from ventilators. The intelligent healthcare agent contains three modules, including the respiratory waveform ontology, ontology construction mechanism, and fuzzy recognition agent, to classify the respiratory waveform. The respiratory waveform ontology represents the respiratory domain knowledge, which will be utilized to classify and recognize the respiratory waveform by the intelligent healthcare agent. The ontology construction mechanism will infer the fuzzy numbers of each respiratory waveform from the patient or respiratory waveform repository. Next, the fuzzy recognition agent will classify and recognize the respiratory waveform into different types of respiratory waveforms. Finally, after the confirmation of medical experts, the classified and recognized results are stored in the classified waveform repository. The experimental results show that our approach can classify and recognize the respiratory waveform effectively.
33337266
A genetic fuzzy agent using ontology model for meeting scheduling system
A Genetic Fuzzy Agent (GFA) using the ontology model for Meeting Scheduling System (MSS) is presented in this paper. The ontology model includes the Fuzzy Meeting Scheduling Ontology (FMSO) and the Fuzzy Personal Ontology (FPO) that can support to construct the knowledge base of the GFA. The FMSO is utilized to record and describe the meeting scheduling domain knowledge for the GFA. In addition, we implement a FMSO editor for generating the Web Ontology Language, OWL, that will be utilized by the GFA. Furthermore, the GFA will infer the suitable meeting time slots based on the ontology model. Moreover, it also adjusts the FMSO and FPO based on the results of the genetic learning mechanism for the next meeting. The experimental results show that our approach can effectively work for MSS.
38422944
Neural-Network-Based Fuzzy Logic Control and Decision System
A general neural-network (connectionist) model for fuzzy logic control and decision systems is proposed. This connectionist model, in the form of feedforward multilayer net, combines the idea of fuzzy logic controller and neural-network structure and learning abilities into an integrated neural-network-based fuzzy logic control and decision system. A fuzzy logic control decision network is constructed automatically by learning the training examples itself. By combining both unsupervised (self-organized) and supervised learning schemes, the learning speed converges much faster than the original backpropagation learning algorithm. The connectionist structure avoids the rule-matching time of the inference engine in the traditional fuzzy logic system. Two examples are presented to illustrate the performance and applicability of the proposed model. >
1173830
A genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks
BitTorrent is a popular, open-source, hybrid peer-to-peer content distribution system that is conducive for distribution of large-volume contents. In this paper, we propose a genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks, which enhances the decision process performed at the tracker for transfer coordination. We also investigate how the strategy affects system throughput and distribution efficiency as well as peer contributions. We show through computer simulations that by increasing content availability to the clients from their immediate neighbors, it can significantly improve the system performance without trading off users' satisfaction. The proposed strategy can significantly improve the efficiency of distribution, especially for low-connectivity peers, and it is suitable to deploy for online decisions
33610569
Compression-based broadcast strategies in wireless information systems
Data delivery is through broadcast in wireless information systems due to the asymmetric communication property. However, broadcasting data easily wastes large access time because the large amount of data pages needs to be broadcast. In this paper we propose three compression-based strategies considering access order to reduce access time. Then, the expected access time of three proposed strategies is also derived by using the probability model. Our analytic and experimental results show that the compression-based broadcast strategies can dramatically reduce the access time for mobile users (MU).
2595872
Schedulability Envelope for Real-Time Radar Dwell Scheduling
This paper proposes novel techniques for scheduling radar dwells in phased array radar systems. In order to handle complex physical characteristics such as dwell interleaving, transmitting duty cycle constraint, and energy constraint, we propose a notion of schedulability envelope. The schedulability envelope designed offline hides the details of complex radar dwell scheduling and provides a simple measure for the schedulability check. Using the schedulability envelope, the proposed technique can efficiently perform the admission control for dynamic target tracking tasks. The simulation results show that the proposed approach can significantly improve the system utilization by taking advantage of dwell interleaving while guaranteeing the schedulability and physical constraints
39638713
Robust H∞ fuzzy static output feedback control of T-S fuzzy systems with parametric uncertainties
This paper addresses robust H"~ fuzzy static output feedback control problem for T-S fuzzy systems with time-varying norm-bounded uncertainties. Sufficient conditions for synthesis of a fuzzy static output feedback controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). In comparison with the existing literatures, the proposed approach not only simplifies the design procedure but also achieves a better H"~ performance. Three drawbacks existing in the previous papers such as coordinate transformation, same output matrices and BMI problem have been eliminated. The effectiveness of the proposed design method is demonstrated by an example for the control of a truck-trailer system.