This paper deals with the partial target coverage (PTC) problem in wireless sensor networks with the objective of optimizing network lifetime. We first build a linear programming formulation, which takes total time a ...
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This paper deals with the partial target coverage (PTC) problem in wireless sensor networks with the objective of optimizing network lifetime. We first build a linear programming formulation, which takes total time a sensor spends on covering some targets into consideration, in order to obtain a lifetime upper bound. Then, based on the information of this formulation, we develop a sensor assignment algorithm to seek an optimal time table meeting the lifetime upper bound. A formal proof of optimality is given. We compare the proposed algorithm with a state-of-the-art algorithm: column generation approach and show that the proposed algorithm significantly outperforms in terms of computational time. Experiments have been conducted to study the effect of network parameters on network lifetime and interesting insights have been offered.
This paper presents a Park transform-based method for preprocessing stator current data from a motor and transforming it into a form that is useful for fault detection and diagnostics. The proposed method generates po...
This paper presents a Park transform-based method for preprocessing stator current data from a motor and transforming it into a form that is useful for fault detection and diagnostics. The proposed method generates power signatures that are invariant to the initial electrical angle of the voltage when the motor is connected to the utility, and can also adapt to variations in the electrical angle of the supply voltage over time. A modified nonlinear least squares algorithm identifies and tracks the parameters of the supply voltage over time, ensuring that the supply voltage and the argument of the Park transformation remain synchronized. Experimental results are presented that illustrate the method's effectiveness for identifying changes in the mechanical load on a 3/4 HP refrigeration compressor.
An analytic method to evaluate frequency dependent losses in on-chip DC-DC buck converters is presented in this paper. These converters feature high switching losses caused by the skin effect in the package inductors....
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An analytic method to evaluate frequency dependent losses in on-chip DC-DC buck converters is presented in this paper. These converters feature high switching losses caused by the skin effect in the package inductors. The frequency dependent air-core inductor model is shown to be critical in determining the optimal switching frequency. A general RLC parameter extraction method is also described. Considering the skin effect results in a 15% reduction in overall DC-DC converter losses. The proposed approach focuses on decreasing ripple current related losses, which are dominant in the target operating condition. Consequently, to obtain optimal efficiency, the switching frequency increases as the load current decreases. An intuitive explanation for this surprising result is that switching losses rise linearly with frequency whereas ripple losses decrease as n 1.5 . A SPICE based circuit model of a DC-DC converter is applied to validate the proposed analytic method.
In order to improve the detection rate of T wave, and to solve the problem that the back propagate neural network (BPNN) is invalid when these initial weight and threshold values of BP neural network are chosen impert...
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In order to improve the detection rate of T wave, and to solve the problem that the back propagate neural network (BPNN) is invalid when these initial weight and threshold values of BP neural network are chosen impertinently (Objective), Genetic Algorithms (GA)'s characteristic of getting whole optimization value was combined with BP's characteristic of getting local precision value with gradient method. After getting an approximation of whole optimization value of weight and threshold values of BP NN by GA, the approximation was used as first parameter of BP neural network, to train (educate) the BPNN again (in other words, learning). The educated BPNN was used to recognize T wave of electrocardiogram (ECG). In order to improve the detection rate of T wave ,making full use of the character that multi-scales changing rules of Wavelet Transform (WT)'s mould max value pairs can indicate signal break points, combining with body physiology synthesis strategy practice, T wave in ECG signal was detected. At the same time, with the help of the educated BP neural network, T wave was confirmed (Methods). Experiment results shown that this method was useful and applicable, and the detection right rate of T wave was above 98% for the MIT database (Results). It is concluded that the combination (WT, GA, BPNN) makes BP neural network to recognition T wave better (Conclusions).
The worldwide Digital Signage market has been getting increasingly popular in recent years. Nevertheless, for service providers, the Digital Signage business is still not easy to manage and time-consuming to operate. ...
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The worldwide Digital Signage market has been getting increasingly popular in recent years. Nevertheless, for service providers, the Digital Signage business is still not easy to manage and time-consuming to operate. In this paper, based on the GPS and wireless infrastructure, we present a mobile location-aware digital signage system (LDSS). Through the centralized system architecture, the applications for the Digital Signage can be expanded to various advertising vehicles including buses and other mobile advertising vehicles. Also, we present an advertisement recommendation algorithm, by which the advertisement can be broadcasted in the right markets more effectively. Evidenced by simulated experiments and analysis, compared with traditional region trigger advertising, sequential advertising and random advertising, our advertisement recommendation algorithm can effectively reach to the key target audiences in planned regions, while show excellent ability to differentiate markets in unplanned regions reaching to the target consumer groups as well.
Disturbance fields in the coal mineral well give a so serious problem on the work of general electric investigation that sometime process of observing useful signal cannot be finished. For extracting weak effective si...
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To enhance the capacity of wireless mesh networks,a key technique is widely investigated which is the usage of multi-radio and multi-channel *** this paper,a new parallel scheduling system is proposed which exploits M...
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To enhance the capacity of wireless mesh networks,a key technique is widely investigated which is the usage of multi-radio and multi-channel *** this paper,a new parallel scheduling system is proposed which exploits MAC diversities by transmitting packets on the radios *** with conventional packet transmission which follows 'one flow one radio',the new system uses radio diversity to transmit the packets on different radios *** kernel components of this system are selection module and schedule module.A localized selecting algorithm is implemented in the selection model to choose the right radios based on the quality of wireless links; two distributed packet-scheduling algorithms are optional with the schedule ***,a routing metric adapting this system is *** have carried out a comprehensive performance evaluation of this system using *** results show that it can successfully harness diversity of multi-radio and multi-channel to provide considerable improvements over a baseline multi-channel system in several situations.
The network model bases upon the energy hub concept, which was developed by the Vision of Future Energy Networks” (VoFEN) research group at ETH Zurich in the last years. Keynote of the concept is a combined optimizat...
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The network model bases upon the energy hub concept, which was developed by the Vision of Future Energy Networks” (VoFEN) research group at ETH Zurich in the last years. Keynote of the concept is a combined optimization of different energy carrier. Synergetic effects are expected to give unusual optimization results, when allowing any possible energy conversion inside a specific area that constitute the hub. Costs for the energy consumption or production are generally used as the optimization criteria. Any technologies for conversion and storage are integrated in a coupling matrix, which links input and output. This paper deals with an extension to the optimization part by merging the network flows with the pricing of grid costs. The impact of network flow pricing is at first derived from theory, then translated into the energy hub concept and finally illustrated in an example.
Spino Cerebellar Ataxia type 2 is an autosomal dominant cerebellar hereditary ataxia with the highest prevalence in Cuba. Typical symptoms in patients of SCA2 ataxia include modifications in latency, peak velocity, an...
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Spino Cerebellar Ataxia type 2 is an autosomal dominant cerebellar hereditary ataxia with the highest prevalence in Cuba. Typical symptoms in patients of SCA2 ataxia include modifications in latency, peak velocity, and deviation in visual saccadic movements. After applying some electro-oculography based tests to both healthy and SCA2 afflicted individuals, differences in saccade morphology were found, mainly for 60° of stimulus amplitude. In this work, independent component analysis (ICA) is used to decompose the pulse and step components for the control of saccadic ocular movements, finding significant differences in time and amplitude ratio of both components. The obtained results point out the validity of the proposed methodology in order to study the effects of ataxia SCA2 in the oculomotor system.
In Code Division Multiple Access (CDMA) systems, the orthogonality of the spreading codes used to achieve multiple access over a channel is severely degraded due to multi-path interference. Expensive equalization tech...
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In Code Division Multiple Access (CDMA) systems, the orthogonality of the spreading codes used to achieve multiple access over a channel is severely degraded due to multi-path interference. Expensive equalization techniques are needed to recover the transmitted signal. The Linear Minimum Mean Square Error (LMMSE) equalizer is a sub-optimal equalizer that is a good compromise between computational complexity and communication system performance. It uses computationally-intensive matrix inversion operations to perform equalization. In this paper, we address the computational challenges of implementing the LMMSE equalizer on Software Defined Radio (SDR) platforms. SDR platforms are favored by the wireless industry due to their significant benefits of reduced development costs and accelerated time-to-market. We present COordinate Rotation DIgital computer (CORDIC) Instruction Set architecture (ISA) extensions that speed up the LMMSE equalization algorithm. The costs and benefits of the ISA extensions are evaluated on the Sandbridge Sandblaster 3000 (SB3000) low-power, multithreaded SDR processor. The proposed ISA extensions provide significant performance improvements with little hardware overhead, while improving the accuracy of the LMMSE Equalizer.
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