Energy efficiency and energy balance are two important issues for wireless sensor networks. In previous clustering routing algorithms, multihop transmission, sleep scheduling, and unequal clustering are always used to...
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Energy efficiency and energy balance are two important issues for wireless sensor networks. In previous clustering routing algorithms, multihop transmission, sleep scheduling, and unequal clustering are always used to improve energy efficiency and energy balance. In these algorithms, only the cluster heads share the burden of data forwarding in each round. In this paper, we propose a flow-partitioned unequal clustering routing (FPUC) algorithm to achieve better energy efficiency and energy balance. FPUC consists of two phases: clustering and routing. In the clustering phase, the competition radius is computed according to the node density and the distance from sensor nodes to the sink. The sensor nodes that have more residual energy and larger overlapping degree have higher probability to be selected as cluster heads. In the routing phase, each cluster head first finds the gateway nodes and then distributes the data flow to each of its gateway nodes depending on residual energy. After that, each gateway node forwards the data to the next hop with minimum cost. Two metrics called network lifetime and coverage lifetime are used to compare the performance of FPUC with that of the existing ones. Simulation results show that FPUC can achieve longer network lifetime and coverage lifetime than previous algorithms.
It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed. The extreme learningmachine (ELM) is a new single hidden layer feedforward neu...
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It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed. The extreme learningmachine (ELM) is a new single hidden layer feedforward neural network method aiming at improving the training speed. Nowadays ELM algorithm has received wide application with its good generalization performance under fast learning speed. However, there are still several problems needed to be solved in ELM. In this paper, a new improved ELM algorithm named R-ELM is proposed to handle the multicollinear problem appearing in calculation of the ELM algorithm. The proposed algorithm is employed in bearing fault detection using stator current monitoring. Simulative results show that R-ELM algorithm has better stability and generalization performance compared with the original ELM and the other neural network methods.
In this study, algorithms for directional relays using only current measurements are presented. Developed for radial distribution networks, these algorithms will determine fault direction based on ratios between varia...
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In this study, algorithms for directional relays using only current measurements are presented. Developed for radial distribution networks, these algorithms will determine fault direction based on ratios between variations of sequence currents during and before faults: Delta I-2/Delta I-0 ratio for line-to-ground faults and the Delta I-2/Delta I-1 ratio for line-to-line faults. The ratios are used as input of a support vector machine classifier, which was trained beforehand thanks to simulation tools. The classifier classifies ratios into two categories, according to the fault location: upstream or downstream towards the relay. Test results from simulations show good performances of the algorithms in most cases, with the presence of different distributed generation technologies. Moreover, impact of certain factors on algorithms, such as measurement errors, high-impedance faults or network reconfiguration, is studied. Finally, the implementation of algorithms is also discussed.
This paper proposes a highly efficient denoising technique in restoring document images that have been corrupted by impulse noise. The proposed algorithm consists of a number of shells and is based on the connectivity...
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This paper proposes a highly efficient denoising technique in restoring document images that have been corrupted by impulse noise. The proposed algorithm consists of a number of shells and is based on the connectivity principle;whereby, pixels that have connections with at least one other pixel in each of the consecutive shells are deemed noise-free pixels. Simulation results indicate that the new denoising method is not only useful in eliminating the noise efficiently;it also keeps the fine details of the image. (C) 2014 Elsevier Ltd. All rights reserved.
This paper introduces a framework that tackles the costs in area and energy consumed by methodologies like spatial or temporal redundancy with a different approach: given an algorithm, we find a transformation in whic...
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This paper introduces a framework that tackles the costs in area and energy consumed by methodologies like spatial or temporal redundancy with a different approach: given an algorithm, we find a transformation in which part of the computation involved is transformed into memory accesses. The precomputed data stored in memory can be protected then by applying traditional and well established ECC algorithms to provide fault tolerant hardware designs. At the same time, the transformation increases the performance of the system by reducing its execution time, which is then used by customized software-based fault tolerant techniques to protect the system without any degradation when compared to its original form. Application of this technique to key algorithms in a MP3 player, combined with a fault injection campaign, show that this approach increases fault tolerance up to 92%, without any performance degradation. (C) 2013 Elsevier Ltd. All rights reserved.
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mat...
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In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm. (C) 2014 Elsevier Ltd. All rights reserved.
The main objective of compact device modelling is to perform the best possible fitting of the model to the measured characteristics. To do so, there are some parameters in the models that must be adjusted to the actua...
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The main objective of compact device modelling is to perform the best possible fitting of the model to the measured characteristics. To do so, there are some parameters in the models that must be adjusted to the actual values used in the technology, plus some other parameters that are used to overcome some of the limitations of the assumptions used in the model development. Obtaining the first set is usually straightforward, whereas determining the second set is more difficult, because the extraction methods are not always efficient and, moreover, there are parameters that are correlated with others, complicating the whole issue. Moreover, there may be parameters that are not relevant for the specific technology. If one could be able to determine the importance of different parameters, then effort could be better directed by dedicating more effort to the most important parameters. A method to order a list of given model parameters using the calculated importance as the criterion is proposed. This importance is calculated using a modification of the Google PageRank algorithm.
Acoustic and vibration control for an underwater structure under mechanical excitation has been investigated by using negative feedback control algorithm. The underwater structure is modeled with cylindrical shells, c...
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Acoustic and vibration control for an underwater structure under mechanical excitation has been investigated by using negative feedback control algorithm. The underwater structure is modeled with cylindrical shells, conical shells, and circular bulkheads, of which the motion equations are built with the variational approach, respectively. Acoustic property is analyzed by the Helmholtz integration formulation with boundary element method. Based on negative feedback control algorithm, a control loop with a coupling use of piezoelectric sensor and actuator is built, and accordingly some numerical examples are carried out on active control of structural vibration and acoustic response. Effects of geometrical and material parameters on acoustic and vibration properties are investigated and discussed.
For a particular two-parameter algebraic program model, two fundamental problems are solved: the recognition of the equivalence of program schemas in this model and the construction of a complete system of equivalent ...
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For a particular two-parameter algebraic program model, two fundamental problems are solved: the recognition of the equivalence of program schemas in this model and the construction of a complete system of equivalent transformations (ETs) of program schemas in the model. The solution is performed by methods developed for one-parameter algebraic program models. This summarizes previous studies of this model. An important functional feature of the model is revealed: the existence of several canonical forms for the representation of schemas in their equivalence class.
The problem of preemptive scheduling in a real-time multiprocessor computing system with release time/deadline intervals is investigated. Approximate algorithms based on the generalization of a single-processor algori...
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The problem of preemptive scheduling in a real-time multiprocessor computing system with release time/deadline intervals is investigated. Approximate algorithms based on the generalization of a single-processor algorithm of relative priority are developed and compared to the exact maximum flow algorithm. An algorithm has been developed for the case where requests for the tasks occur periodically with given periods. An algorithm for determining the values of the processor performance for which there exists an admissible schedule for a given assembly of tasks with release time/deadline intervals has been developed.
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