In recent years, with the improvement of health awareness, people have paid more and more attention to proper meal. Existing research has shown that a proper meal can help people prevent lifestyle diseases such as diabetes. In this research, by attaching sensors to the tableware, the information during the meal can be captured, and after processing and analyzing it, the meal information, such as time and sequence of meal, can be obtained. This paper introduces how to use supervised learning and multi-instance learning to deal with meal information and a detailed comparison is made. Three supervised learning algorithms and two multi-instance learning algorithms are used in the experiment. The experimental results showed that although the supervised learning algorithms have achieved good results in F-score, the multi-instance learning algorithms have achieved better results not only in accuracy but also in F-score.

The Asynchronous Transfer Mode (ATM) technique has been accepted as a basis for the future B-ISDN networks. In ATM networks, all information is packetized and transferred in small packets of fixed length, called cells. The packetized information transfer, without flow control between the user and the network and the use of statistical multiplexing, results in a need of a policing mechanism to control the traffic parameters of each virtual connection in order to guarantee the required quality of service (QoS). Policing of the peak cell rate is generally not complex and can be achieved by using a cell spacer or other policing mechanisms (PMs). Monitoring of the mean cell rate is more difficult, but is intended to improve the link utilization when it has to handle bursty traffic sources. Conventional PMs, such as the Leaky Bucket Mechanism (LBM) and Window Mechanisms (WMs), are not well suited to the bursty nature of the sources supported by ATM networks, therefore intelligent PMs are needed. In this paper, we propose a Fuzzy Policing Mechanism (FPM) for multimedia applications over ATM networks. We consider the case of still picture source control. The performance evaluation via simulation shows that the FPM efficiently controls the mean cell rate of the still picture source. The proposed FPM shows a good response behavior against parameter variations and the selectivity characteristics approach very close to the ideal characteristic required for a PM. The FPM has a better characteristic compared with the LBM.