In this paper, the problem of forest fire is considered and a comprehensive system is proposed with the use of wireless sensor network for real-time forest fire detection. The wireless sensor network can give more acc...
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In this paper, the problem of forest fire is considered and a comprehensive system is proposed with the use of wireless sensor network for real-time forest fire detection. The wireless sensor network can give more accurate detection of forest fire danger rate over traditional monitoring approaches like lookout towers and satellite based monitoring. This proposed framework mainly describes the data collection from designed data acquisition system and then its classification. The wireless transmission of sensor node data is done using BTBee module. Also artificial neural networks (ANN) approach, i.e. support vector machine (SVM) is applied for classification of collected data. Classification accuracy is evaluated and compared for various Kernel functions including multilayer perceptron (MLP), polynomial, quadratic and radial basis function (RBF).
This paper presents a basic research results to visualize the micro-movement of formant tracks for the purpose of using it to analyze speech signal on the research of speech analysis and synthesis etc. Current analysi...
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ISBN:
(纸本)9781479927654
This paper presents a basic research results to visualize the micro-movement of formant tracks for the purpose of using it to analyze speech signal on the research of speech analysis and synthesis etc. Current analysis method on formant is mainly focusing on analysis of static statistical characteristics. But dynamic information about changing vowels is hard to acquire using conventional statistical results such as mean, variance etc. In this experiment we propose a new visualization method to display the dynamic behavior of vowel changes according to the micro movement of formant on vowel space.
In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for r...
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In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for real company which presents a major problem for controlling the quality level of production. HFS structure has reduced complexity in the number of input and output meta-levels of hierarchy. Also NFHH model has presented better performance in terms of precision and number of parameters without losing the universal approximation property of neural networks (NN) and fuzzy systems.
Almost all people who get laryngeal cancer are treated by laryngectomy. However, this treatment affects their voice since the larynx will be removed. This research presents a technique which can recover their voice to...
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Almost all people who get laryngeal cancer are treated by laryngectomy. However, this treatment affects their voice since the larynx will be removed. This research presents a technique which can recover their voice to communicate with others again. The technique is esophageal speech;this technique does not require any additional device but it needs only a continuously training from speech therapist. In additional, the training software for esophageal speech is designed and developed based on three speech characteristics which are tempo, loudness and duration of speech. For more attractive, we developed into computer game-based. The experiment is divided by two groups of users;normal speakers and esophageal speakers. The results of experiments are evaluated by using Mean Opinion Score, and the score are 4 from esophageal speakers and 3.7 from normal speakers.
This paper considers the problem of state estimation and unknown input reconstruction of a class of connected heterogeneous LTI MIMO systems. Local high order sliding mode observers at each node of the network are des...
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This paper considers the problem of state estimation and unknown input reconstruction of a class of connected heterogeneous LTI MIMO systems. Local high order sliding mode observers at each node of the network are designed for this purpose. The proposed method, under some network structural conditions, is inherently robust, nonlinear and totally independent of the time-varying network topology. Knowledge of the number of nodes that belong to the network is not required. At the supervisory level, decentralized control signals are computed based on the state estimates in order to operate the networking synchronization. By mean of simulation, the effectiveness of the proposal procedure is shown.
The control of a Rotary Inverted Pendulum (RIP) is a well-known and a challenging problem that serves as a popular benchmark in modern control system studies. The task is to design controllers which drives the pendulu...
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The control of a Rotary Inverted Pendulum (RIP) is a well-known and a challenging problem that serves as a popular benchmark in modern control system studies. The task is to design controllers which drives the pendulum from its hanging-down position to the upright position and then hold it there. The swing up is achieved using an energy based controller. In energy based control the pendulum is controlled in such a way that its energy is driven towards a value equal to the steady-state upright position. Then a mode controller switches between the swing-up controller and stabilizing controller near the upright position. For stabilization control, two control techniques are analyzed. Firstly, a sliding mode controller (SMC) is designed to stabilize the pendulum. Secondly, a state feedback controller is designed that would maintain the pendulum upright and handle disturbances up to a certain point. The state feedback controller is designed using the linear quadratic regulator (LQR). The responses of the LQR controller and SMC controller are compared in simulation.
In this paper, a data reduction technique is proposed for incremental learning of SVDD. Two methods are used in order to train a lot of data. One method is to remove redundant data. The other one is to remove the data...
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This paper presents the design of a robust linear controller that can be used for trajectory following and maneuvering of fixed-wing aircraft using Nonlinear Dynamic Inversion (NDI) principles. The design addresses co...
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ISBN:
(纸本)9781467359108
This paper presents the design of a robust linear controller that can be used for trajectory following and maneuvering of fixed-wing aircraft using Nonlinear Dynamic Inversion (NDI) principles. The design addresses control coupling to exploit multiple redundant controls. It can also be easily extended to state decoupling. The design procedure exploits the nature of the equations of motion written in the wind axis resulting in a cascaded linear controller structure with inner and outer loops. A systematic methodology is evolved which uses only the relevant stability and control derivatives in the control synthesis, as opposed to the inversion of the complete nonlinear equations used in conventional NDI designs. The tuning of the control gains is based on the requirements of adequate trajectory following and robustness to control surface failures. Finally, it is shown how a series of controllers can be derived depending on the sensor complement available on the aircraft. The proposed approach is ideal for fixed-wing Unmanned Aerial Vehicles (UAVs).
The main aim of this work is to keep the interacting liquid level and temperature parameter at the desired value. This article presents Kravari's algorithm, Generic Model control (GMC) and Hischorn's algorithm...
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A new method to identify the spatial dependent parameters describing the heat transport, i.e. diffusion and convection, in fusion reactors is presented. These parameters determine the performance of fusion reactors. T...
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ISBN:
(纸本)9781479915583
A new method to identify the spatial dependent parameters describing the heat transport, i.e. diffusion and convection, in fusion reactors is presented. These parameters determine the performance of fusion reactors. The method is based on local transfer functions, which are defined between two measurement locations. Estimation of the local transfer functions results in a model of the spatial dependent diffusion and convection. The parameters of the local transfer functions are estimated using Maximum Likelihood Estimation in the frequency domain. This is necessary, because both measurements (input and output of the transfer function) contain noise. Moreover, confidence bounds and validation tests can be used in this framework. Finally, experimental results are presented, which show that the diffusion and convection can be estimated. In this case, the uncertainty bounds are too large on the convection to conclude its presence.
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