293 research outputs found

    A novel approach to security enhancement of chaotic DSSS systems

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    In this paper, we propose a novel approach to the enhancement of physical layer security for chaotic direct-sequence spread-spectrum (DSSS) communication systems. The main idea behind our proposal is to vary the symbol period according to the behavior of the chaotic spreading sequence. As a result, the symbol period and the spreading sequence vary chaotically at the same time. This simultaneous variation aims at protecting DSSS-based communication systems from the blind estimation attacks in the detection of the symbol period. Discrete-time models for spreading and despreading schemes are presented and analyzed. Multiple access performance of the proposed technique in the presence of additional white Gaussian noise (AWGN) is determined by computer simulations. The increase in security at the physical layer is also evaluated by numerical results. Obtained results show that our proposed technique can protect the system against attacks based on the detection of the symbol period, even if the intruder has full information on the used chaotic sequence.Peer ReviewedPostprint (author's final draft

    Application of AHP algorithm on power distribution of load shedding in island microgrid

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    This paper proposes a method of load shedding in a microgrid system operated in an Island Mode, which is disconnected with the main power grid and balanced loss of the electrical power. This proposed method calculates the minimum value of the shed power with reference to renewable energy sources such as wind power generator, solar energy and the ability to control the frequency of the generator to restore the frequency to the allowable range and reduce the amount of load that needs to be shed. Computing the load importance factor (LIF) using AHP algorithm supports to determine the order of which load to be shed. The damaged outcome of load shedding, thus, will be noticeably reduced. The experimental results of this proposed method is demonstrated by simulating on IEEE 16-Bus microgrid system with six power sources

    VLSP Shared Task: Named Entity Recognition

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    Named entities (NE) are phrases that contain the names of persons, organizations, locations, times and quantities, monetary values, percentages, etc. Named Entity Recognition (NER) is the task of recognizing named entities in documents. NER is an important subtask of Information Extraction, which has attracted researchers all over the world since 1990s. For Vietnamese language, although there exists some research projects and publications on NER task before 2016, no systematic comparison of the performance of NER systems has been done. In 2016, the organizing committee of the VLSP workshop decided to launch the first NER shared task, in order to get an objective evaluation of Vietnamese NER systems and to promote the development of high quality systems. As a result, the first dataset with morpho-syntactic and NE annotations has been released for benchmarking NER systems. At VLSP 2018, the NER shared task has been organized for the second time, providing a bigger dataset containing texts from various domains, but without morpho-syntactic annotation. These resources are available for research purpose via the VLSP website vlsp.org.vn/resources. In this paper, we describe the datasets as well as the evaluation results obtained from these two campaigns
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