Attitude estimation has a wide range of applications including aerial (UAVs for example), underwater (ROVs for instance), navigation systems, robotics, games, augmented reality system, industrial and so on. Extensive ...
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In this paper, a new DSC-PLL(Delayed Signal Cancellation Phase Locked Loop) with FLL(Frequency Locked Loop) based on RDFT(recursive discrete fourier transform) method is proposed for coping with frequency variation. T...
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ISBN:
(纸本)9781467395519
In this paper, a new DSC-PLL(Delayed Signal Cancellation Phase Locked Loop) with FLL(Frequency Locked Loop) based on RDFT(recursive discrete fourier transform) method is proposed for coping with frequency variation. This method shows significant performance improvement for detection of fundamental positive sequence component voltage when the grid voltage is polluted by grid harmonics and frequency variation. The frequency detection technique of DSC-PLL tracks frequency drift by the RDFT. These compensation algorithms can correct for discrepancies of changing the frequency within maximum 28ms and improve traditional DSC-PLL. To verify feasibility of the proposed DSC-PLL, Matlab/Simulink results show good agreement with the analysis.
This paper presents an isolated type of single-phase matrix converter topology for PHV/EV on-board battery chargers. The proposed converter is comprised of a full bridge inverter, a high frequency transformer and a ma...
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Existing software allows the development of high quality interactive applications that permit their implementation in laboratories, both virtual and remote. To perform an experiment, the user needs to know how these a...
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Traffic congestions have huge impact on urban transportation and are even more problematic when emergency vehicles are present, their fast travel requirements disrupting regular traffic. The aim of this study is to fo...
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Traffic congestions have huge impact on urban transportation and are even more problematic when emergency vehicles are present, their fast travel requirements disrupting regular traffic. The aim of this study is to formulate an agent based simulation perspective on aiding the design of complex and distributed controlsystems, such as the one facilitating the arrival of the emergency vehicles to accident sites. Thus, we provide a user friendly method for validation of traffic controlsystems that supports interdisciplinary design. In particular, such a simulation model can be easily used by transportation engineers not acquainted with the mechanics of controlsystems, as it allows for empirical transfer of knowledge from the ITS field into controller synthesis methodology.
The service-oriented environment offers the opportunity to create new applications, by combining existing applications offered as services, in order to react to the business' increasing pressure of quickly deliver...
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The service-oriented environment offers the opportunity to create new applications, by combining existing applications offered as services, in order to react to the business' increasing pressure of quickly delivering new applications. With a large number of web services offering the same functionality, choosing the web services that meet best the client's quality of service (QoS) requirements is a very important task. We introduce a QoS-aware end to end web service composition approach that handles all the stages from the web service discovery step, to the actual binding of the services. This approach uses our method of expressing nonfunctional preferences, which requires minimal effort on the part of the clients, but offers great flexibility in managing trade-offs. We define a QoS preferences ontology and use it in our semantic web service selection to choose an initial candidate list of services for every task in the orchestration model. Then, one concrete service is chosen from each candidate list and is boand to the corresponding task. This step involves computing and comparing the aggregated QoS of the resulting composite services. The selection is performed using a genetic algorithm.
Big data is one of the hottest topics in information science. It has become the key for biological and medical discovery and research, making developing new methods for data management, analysis and accessibility a gr...
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ISBN:
(纸本)9781467375467
Big data is one of the hottest topics in information science. It has become the key for biological and medical discovery and research, making developing new methods for data management, analysis and accessibility a great challenge in the field. This study proposes an integrated gene analysis approach, in terms of classification and prediction methods for understanding, analyzing and interpretation of biological data related to cancer. The final aim of this study is to predict and classify several subtypes of cancer, based on gene expression.
Artificial neural networks are widely used in classification problems due to their adaptability. In this paper, an original multi-layer perceptron is used to automatically detect meteors within radio recordings. The a...
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Artificial neural networks are widely used in classification problems due to their adaptability. In this paper, an original multi-layer perceptron is used to automatically detect meteors within radio recordings. The approach presented can be divided into two stages: data preparation and meteor detection. In the data preparation stage, samples are built from a number of the spectrogram's vertical lines. During the meteor detection stage, neural networks are trained using the inputs previously extracted, and their meteor detection capabilities are tested. The rate of correctly detected meteor samples by the neural networks trained in this paper is over 80%.
The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when user...
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The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when users are searching for specific information on a given topic. Another problem is the massive increase in the number of pages to be indexed by Web search systems. In this research, two steps for Web Crawling are used to decrease these difficulties. First step is the feature selection for the datasets used. A proposed algorithm of feature selection, which uses the Document Frequency technique for the term in the category, is presented. Second step is Web page classification. Two famous techniques of Web page classification are used: (i) Support Vector Machine and (ii) Naïve Bayes Classifier. It is concluded that the proposed algorithm, using Document Frequency technique, reduces the redundancy during feature selection and increases accuracy during Web page classification. Complete evaluation is performed, in JAVA, to indicate the effectiveness of our proposed algorithm.
The automatic meteor detection solution presented in this paper uses a self-organizing map to analyze radio spectrogram data and detect the meteor samples found within. This artificial neural network is trained using ...
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The automatic meteor detection solution presented in this paper uses a self-organizing map to analyze radio spectrogram data and detect the meteor samples found within. This artificial neural network is trained using data samples extracted from spectrograms of radio recordings using a rectangular sliding window. Several tests were run to find the optimal neural network topology and duration of training. The trained network is then analyzed using a new set of data and its performance is manually validated. Testing has shown that the proposed self-organizing map solution produces significant meteor detection results.
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