• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.135-142
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• 2010

QoS in the proxy system are under heavy influence from interferences such as congestion, latency, and retransmission. Also, multi-level streaming services affects from temporal synchronization, which lead to degrade the service quality. This paper proposes a new segment-based buffer management mechanism which reduces performance degradation of streaming services and enhances throughput of streaming due to drawbacks of the proxy system. The proposed paper optimizes streaming services by: 1) Use of segment-based buffer management mechanism, 2) Minimization of overhead due to congestion and interference, and 3) Minimization of retransmission due to disconnection and delay. This paper utilizes fuzzy value $\mu$ and cost weight $\omega$ to process the result. The simulation result shows that the proposed mechanism has better performance in buffer cache control rate, average packet loss rate, and delay saving rate with stream relevance metric than the other existing methods of fixed segmentation method, pyramid segmentation method, and skyscraper segmentation method.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.