This paper presents a method for an unsupervised discovery of acoustic patterns in bird vocalisations recorded in real world natural environments. The proposed method employs sinusoidal detection to provide frequency ...
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This paper presents a method for an unsupervised discovery of acoustic patterns in bird vocalisations recorded in real world natural environments. The proposed method employs sinusoidal detection to provide frequency tracks which are used as features to characterise bird tonal vocalisations. A variant of dynamic time warping, capable of searching for multiple partial matchings, is used to segment the data based on these frequency track sequences. Agglomerative hierarchical clustering approach is then employed to cluster recurring segments. Evaluations are performed on audio recordings provided by the Borror Laboratory of Bioacoustics. The obtained results indicate that structurally distinct stereotyped acoustic units can be determined.
Despite the stern actions by governments, road accidents have become unavoidable throughout the world. Hence it is crucial to take care of the safety of drivers. It is where the Vehicular Ad-Hoc Network (VANET) comes ...
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Recently, manifold learning has been widely exploited in pattern recognition and data mining. Local tangent space alignment (LTSA) is a classical non-linear manifold learning method, which is efficient for non-linear ...
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Recently, manifold learning has been widely exploited in pattern recognition and data mining. Local tangent space alignment (LTSA) is a classical non-linear manifold learning method, which is efficient for non-linear dimensionality reduction. However, it fails to learn locally high curvature dataset. To address this problem, this paper describes the data set of the locally curvature by the given parameter and presents a new algorithm called locally minimal deviation space alignment (LMDSA). Considering the low-robust deficiencies in local tangent space, LMDSA can find the locally high curvature while computing locally minimal deviation spaces. The algorithm also reduces the probability of locally high curvature space with parameter control and the joint information between neighborhood information. Then the algorithm applies space alignment technique to reduce dimensionality. Besides the advantages above, LMDSA has the ability to learn sparse dataset. Extensive experiments on both synthetic manifold and real-world images indicate the efficiency of our algorithm. In synthetic manifold, LMDSA is compared with LTSA in two local high curvature datasets and one dataset with a hole. The experimental results show our algorithm learns correct manifold structure in low-dimension space. In sparse real-world datasets, LMDSA outperforms other algorithms in this paper.
The land transportation contribute large amount of CO2 emission due the low conversion efficiency in transport vehicle. Normally, the energy conversion efficiency in road vehicle was presented in term of amount of fue...
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The land transportation contribute large amount of CO2 emission due the low conversion efficiency in transport vehicle. Normally, the energy conversion efficiency in road vehicle was presented in term of amount of fuel per distance within specific condition where it could not be comparable in practice especially in logistic sector that the variation of load factor and dynamic traffic condition were impacted. In this study, the alternative efficiency indicator was proposed with applying kinetic energy concept to formulate road-vehicle efficiency factor (REF) which include dynamic behavior and weight of vehicle. Furthermore, the experimental were taken place in Pahonyothin Rd. (Bangkok, Thailand) including urban and highway with various traffic congestion level. Therefore, the road-vehicle efficiency factor were manipulated and shown that the factor could be used to indicate the efficiency in various types of vehicle. From the tests, the Commonrail Turbo Direct-Injection Diesel technology had highest efficiency while the variable valve timing gasoline engines were better than conventional gasoline engine. Also, the vehicles within same powertrain technology were had same trend of REF. In conclusion, this method could be applied for further vehicle analysis.
It is common that an efficient constrained plant operation under full range of disturbance inputs require meeting different sets of control objectives. This calls for application of model predictive controllers each o...
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Vehicular Ad hoc Networks are emerging class of Mobile Ad hoc Networks that provide wireless communication between vehicles with no need for any fixed infrastructure. It is proven that in highly dynamic vehicular envi...
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Vehicular Ad hoc Networks are emerging class of Mobile Ad hoc Networks that provide wireless communication between vehicles with no need for any fixed infrastructure. It is proven that in highly dynamic vehicular environments beaconless position-based forwarding algorithms are more suitable than the algorithms that use periodic beacon information in their forwarding decisions. However, data packet broadcasting in forwarding mechanism of these algorithms leads to packet duplications in both forwarding area and the destination node and consequently increases the network overhead and wastes available bandwidth. In this paper we propose a new beaconless forwarding algorithm called CBBPF in which data packets are not broadcasted to the neighbors to avoid duplication. The simulative performance evaluation results in highway scenarios show that CBBPF operates properly in terms of packet delivery ratio and average end-to-end delay.
There is a need for displacement and angle measurements in many movable MEMS structures. The use of fibre optical sensors helps to measure micrometre displacements and small rotation angles. Advantages of this type of...
There is a need for displacement and angle measurements in many movable MEMS structures. The use of fibre optical sensors helps to measure micrometre displacements and small rotation angles. Advantages of this type of transducers are their simple design, high precision of processing, low costs and ability of a non-contact measurement. The study shows an analysis of a fibre-optic intensity sensor used for MEMS movable structure rotation angle measurement. An intensity of the light in the photodetector is basically dependent on a distance between a reflecting surface and a head surface of the fibre transmitting arm, and the deflection angle. Experimental tests were made for PMMA 980/1000 plastic fibres, ΘNA=33°. The study shows both analytical and practical results. It proves that calculated and experimental characteristics for the analysed transducers are similar.
3-D Networks-on-Chip (NoC) emerge as a potent solution to address both the interconnection and design complexity problems facing future Multiprocessor System-on-Chips (MPSoCs). Effective run-time mapping on such 3-D N...
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This paper presents a new Rössler chaotic system using exponential nonlinearity and its application to two-channel synchronization. The proposed chaotic system exhibits a chaotic attractor that resembles the orig...
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ISBN:
(纸本)9781467362481
This paper presents a new Rössler chaotic system using exponential nonlinearity and its application to two-channel synchronization. The proposed chaotic system exhibits a chaotic attractor that resembles the original Rössler system with only six-term in three-dimensional ordinary equation systems using the exponential nonlinearity. Chaotic dynamics are described in terms of equilibria, Jacobian matrix, time domain waveforms, chaotic attractors, and bifurcation diagram. The circuit implementation is relatively compact and simple sine the exponential nonlinearity can be achieved by an inherent nonlinearity of single diode. An application to a two-channel secure communication are also demonstrated, showing a fast, low-error and robust synchronization processes.
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