Characterizing user‐perceived impairment events using end‐to‐end measurements

Measures of quality of service (QoS) must correlate to end‐user experience. For multimedia services, these metrics should focus on the phenomena that are observable by the end‐user. Metrics such as delay and loss may have little direct meaning to the end‐user because knowledge of specific coding and/or adaptive techniques is required to translate delay and loss to the user‐perceived performance. Impairment events, as defined in this paper, are observable by the end‐users independent of coding, adaptive playout or packet loss concealment techniques employed by their multimedia applications. Time between impairments and duration of impairments are metrics that are easily understandable by a network user. Methods to detect these impairment events using end‐to‐end measurements are developed here. In addition, techniques to identify Layer 2 route changes and congestion events using end‐to‐end measurements are also developed. These are useful in determining what caused the impairments. End‐to‐end measurements were conducted for about 26 days on 9 different node pairs to evaluate the developed techniques. Impairments occurred at a high rate on the two paths on which congestion events were detected. On these two paths, congestion occurred for 6–8 hours during the day on weekdays. Impairments caused by route changes were rare but lasted for several minutes. Copyright © 2005 John Wiley & Sons, Ltd.     

A joint investigation of misclassification treatments and imbalanced datasets on neural network performance

Two important factors that impact a classification model’s performance are imbalanced data and unequal misclassification cost consequences. These are especially important considerations for neural network models developed to estimate the posterior probabilities of group membership used in classification decisions. This paper explores the issues of asymmetric misclassification costs and unbalanced group sizes on neural network classification performance using an artificial data approach that is capable of generating more complex datasets than used in prior studies and which adds new insights to the problem and the results. A different performance measure, that is capable of directly measuring classification performance consistency with Bayes decision rule, is used. The results show that both asymmetric misclassification costs and imbalanced group sizes have significant effects on neural network classification performance both independently and via interaction effects. These are not always intuitive; they supplement prior findings, and raise issues for the future.     

Oil concentration in liquid refrigerants: in situ measurementConcentration d''huile dans les frigorigènes liquides : mesures sur le terrain

The concentration of oil in refrigerants (while in liquid state) can be measured with an acoustic velocity sensor. The transit time for an acoustic signal can be related to the oil concentration and temperature of the liquid mixture. The performance of the sensor is dependent on the properties of the oil and refrigerant, and their miscibility. In general, a thorough calibration becomes necessary. It is shown in this paper that for concentrations less than 10%, an approximation can be made for the estimate of concentration hence eliminating the need for an elaborate calibration procedure.     

Photochromic properties of polyimide and polysiloxane azopolymers

BACKROUND: One of the most important properties of the azobenzene chromophores is the photochemical trans–cis isomerization induced by UV or visible light. In azopolymers, the photoisomerization induces conformational changes in the polymer chains, which in turn lead to macroscopic variations in the chemical and physical properties of the surroundings and media. RESULTS: This work reports the photochromic behaviour and surface structuring capacity of azopolymers having rigid polyimide and flexible polysiloxane structures, respectively. These polymers have good thermostabilities, with the degradation process starting above 315 °C. The glass transition temperature of the azopolyimide is 228 °C, while that of the azopolysiloxane modified with thymine is 34 °C. CONCLUSION: The experiments show that the azobenzene groups can isomerize even in the case of the rigid polyimide, but the maximum degree of conversion to the cis isomer is less than in the case of the flexible polysiloxane. This behaviour is reversed in solution, probably due to both the thymine and azo group interactions and for conformational reasons. The azopolymers show a good surface structuring capacity. The polysiloxane is more sensitive in the case of low irradiation energy and irradiation time. By increasing the irradiation time for both polymers, the modulation depth increases and has comparable values. Copyright © 2008 Society of Chemical Industry     

A fuzzy inference approach to template-based visual tracking

The tracking of visual features using appearance models is a well studied but still open area of computer vision. In the absence of knowledge about the structural constraints of the tracked object, the validity of the model can be compromised if only appearance information is used. We propose a fuzzy inference scheme that can be used to selectively update a given template-based model in tracking tasks. This allows us to track moving objects under translation, rotation, and scale changes with minimal feature drift. Moreover, no rigidity constraint needs to be enforced on the moving target. Some experiments have been performed using several targets, and the results are very close to the ground truth paths. The computational cost of our approach is low enough to allow its application in real-time tracking using modest hardware requirements.