This paper studies congestion control in high-speed communication networks using Model Predictive Control (MPC). Network traffic is assumed to consist of best-effort and priority traffic sources. An integrated control...
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Frames are a mathematical tool which can represent redundancies in many application problems. In this article, a class of infinite dimensional and bi-directional frames are studied. It is shown that the infinite dimen...
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Two virtual windows are used to determine the path of a single uniformly moving obstacle. If the path of the obstacle crosses the two virtual windows, then its path can be easily determined. A few simulations were imp...
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Most of segmentation methods based on manifold learning utilize globally or locally linear strategies. However, these linear strategies can not cope with the high curvature structure of sequence dataset. Considering t...
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Most of segmentation methods based on manifold learning utilize globally or locally linear strategies. However, these linear strategies can not cope with the high curvature structure of sequence dataset. Considering the continuity of human motion and the local high curvature in human motion sequence, a segmentation method using manifold learning is proposed to deal with the segmentation problem in this paper. The method evaluates the coherence of human motion based on the local warp index of sequence data. As the transition clips between the certain adjacent motion units warp largely, the filtering technique as well as the piecewise linear representation is applied to deal with the motion sequence. The experimental results show that the proposed method combined with the characteristic curves of the dimensionality reduction is effective to the segmentation of the CMU human motion datasets etc.
Outdoor machine vision is getting a concern nowadays. Ranging from surveillance and monitoring system to automotive system such as driver assistance system require vision application or artificial eye to keep monitori...
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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 ...
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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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