Measurement of Internet Protocol Packet Delay Variation (IPDV) is a relevant issue in application involving real time video streaming. Generally, this quantity is compared with predefined thresholds (whose value depen...
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Measurement of Internet Protocol Packet Delay Variation (IPDV) is a relevant issue in application involving real time video streaming. Generally, this quantity is compared with predefined thresholds (whose value depends upon the application requirements) to verify the quality of service to the end user. However, the exceeding of this threshold only for short time intervals and with relatively low repetition rates, generally does not imply a significant decrease of the user perceived quality. Vice-versa, IPDV values not exceeding the admitted threshold but very close to this value for long time intervals and characterized by relatively high repetition rates can significantly affect the user perceived quality. Consequently, a study of the correlation among the measured IPDV values and some performance metrics directly related to the quality perceived by the user has to be accurately investigated. On the other hand, literature concerning with IPDV evaluation does not provide some important information about the measurement procedure, such as measurement rate, how to collect the obtained result in a single estimator, the time interval on which the estimator is evaluated, and so on. Consequently, the absence of these important aspects about the measurement procedure makes very critical the comparison between the evaluated IPDV and the above-mentioned thresholds, thus making even more ambiguous the evaluation of the quality of service to the end user. In this framework, the aim of the paper is to design and fine tune an IPDV estimator able to reliably estimate and detect the objective service degradation from the user perspective.
A significant difficulty associated with achieving high scan speeds in scanning probe microscopes is that the probe is required to scan the sample in a zig-zag (raster) pattern. The fast axis of the scanner is require...
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A significant difficulty associated with achieving high scan speeds in scanning probe microscopes is that the probe is required to scan the sample in a zig-zag (raster) pattern. The fast axis of the scanner is required to track a non-smooth signal that contains frequency components beyond its mechanical bandwidth. Therefore, fast raster scans lead to distortions in the obtained image. This paper proposes analysis and design methods for a nonlinear but smooth scan pattern, known as Lissajous pattern, which enables us to achieve high-quality images at very high scan speeds where raster scanning typically leads to significant image distortions. Criteria are also proposed and formulated for constructing Lissajous trajectory and calculating the parameters and resolution. Together with the implementation of an internal model controller for high precision tracking, the proposed method is successfully employed to scan images in high speeds using a low resonance frequency SPM platform of only 825 Hz.
A wireless relay which forms a one-to-one mapping from the inputs (uplinks) to the outputs (downlinks) is called a multiple-input-multiple-output (MIMO) switch. The MIMO switch carries out precode-and-forward, where a...
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Identification of machine condition is crucial to reduce machine downtime and scrap parts in the manufacturing industries. In this paper, we propose a novel methodology to identify life stage and estimate machine wear...
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Identification of machine condition is crucial to reduce machine downtime and scrap parts in the manufacturing industries. In this paper, we propose a novel methodology to identify life stage and estimate machine wear. The proposed framework is based on stage identification using Support Vector Machines (SVMs) and machine wear estimation using AutoRegressive Moving Average with eXogenous inputs (ARMAX) models. Our proposed framework is evaluated on a high-speed industrial milling machine, and the effectiveness of the proposed methodology in tool wear stage identification and tool wear estimation is verified with experimental results.
A Norm-Optimal Iterative Learning control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties ...
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Peer-to-Peer (P2P) distributed systems have received considerable attention mainly due to their potential for high-performance and high-reliability. Job scheduling in P2P distributed systems is one of the most importa...
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Peer-to-Peer (P2P) distributed systems have received considerable attention mainly due to their potential for high-performance and high-reliability. Job scheduling in P2P distributed systems is one of the most important issues. In this paper, we have evaluated the performance of four job scheduling algorithms named Random, Round Robin, Number of Connections and Server Load in P2P distributed computing environment. The aim of the performance evaluation is to provide a comprehensive view of what performance can be expected from these algorithms in P2P systems in terms of CPU utilization, task processing, traffic received and traffic sent at different load scenarios. We used OPNET modeler to build the simulation model for FTP application on the P2P distributed systems. The output of the performance comparison illustrates different QoS (Quality of Service) aspects of these basic algorithms under different workloads and traffic settings. The results show that the performance of each algorithm changes according to the operational environment setting. The simulation results show that the Server Load-based scheduling algorithm has the best performance among the four algorithms followed by the Number of Connections-based scheduling algorithm. Simulations also show that the Server Load scheduling policy is not suitable for heavy load situations and the Random algorithm is suitable for some settings, especially in the low load situation.
The inverse mapping in MagnetoEncephaloGraphy involves localizing neuronal activity of the gray matter tissue from measured signals around the head. The search space of the inverse mapping is conventionally represente...
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ISBN:
(纸本)9781467331289
The inverse mapping in MagnetoEncephaloGraphy involves localizing neuronal activity of the gray matter tissue from measured signals around the head. The search space of the inverse mapping is conventionally represented in 3-D Cartesian coordinates including the cortical volume, or alternatively, 2-D manifold describing the cortical tissue. 3-D Cartesian coordinates does not suit sparse regularization of the inverse mapping in multi-resolution source domains. On the other hand, boundary surface of the cortex, represented as triangulated mesh, is used as the search space in some other inverse mapping techniques. However, this surface does not represent depth of the cortex. Moreover, to represent neuronal activity in embedded signal dictionaries, convoluted manifold should be gridded. In this paper we propose to use medial surface as the best surface descriptor of the cortical tissue. Furthermore, manifold gridding is constructed by defining bijective mapping between a flattened parameterized domain and convoluted surface. Signal bases are defined conventionally in the parameterized domain and mapped to the cortical volume by means of the bijective mapping. Medial surface of the cortex tissue, represented as triangulated mesh, is extracted by gradient-based search algorithm. Source localization, for simulated neuronal activity, is performed in real head model extracted from magnetic resonance images. Sparse estimated source of the inverse mapping are compared on volume, boundary surface, and medial surface domains. Simulation results confirm advantages of surface over volume domain. Performnace measures of source localization proves the medial surface as the best surface describing the cortex volume.
This paper deals with a new approach for evaluation of e-learning programs. Based on methods of general measure theory an evaluation model is developed which can be used for assessment of complex logical target struct...
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ISBN:
(纸本)9781467317726
This paper deals with a new approach for evaluation of e-learning programs. Based on methods of general measure theory an evaluation model is developed which can be used for assessment of complex logical target structures in context of e-learning programs. Basic idea of presented method is the embedding of aims to be reached in an adapted logical structure which contains the key and sub targets of evaluation. For such structures a measure theoretical scoring model is developed. It is described how to given observation data, obtained with an adjusted assessment checklist, a score value for evaluation of an e-learning program can be computed. The presented model is very versatile. By the measure theoretical background the evaluation method becomes open, comprehensible and traceable.
In this article, synchronization of FitzHugh-Nagumo (FHN) neurons is considered. Adaptive controller based on active compensation is adopted to drive the slave neuron to track the master neuron. Sufficient condition f...
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In this article, synchronization of FitzHugh-Nagumo (FHN) neurons is considered. Adaptive controller based on active compensation is adopted to drive the slave neuron to track the master neuron. Sufficient condition for asymptotic stability of the close-loop system is derived. Numerical simulation results are given to confirm the adaptive controller is valid.
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