By Toshio Fukuda (auth.), Jiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida (eds.)
The prior few years have witnessed swift scienti?c and technological devel- ments in human-centered, seamless computing environments, interfaces, de- ces, and platforms with functions starting from enterprise and conversation to leisure and studying. those advancements are jointly top charac- rized as energetic Media know-how (AMT), a brand new quarter of data expertise and computing device technology that emphasizes the proactive, seamless roles of interfaces and structures in addition to new electronic media in all points of human lifestyles. This - lume comprises the papers awarded on the 6th foreign computing device technological know-how convention: energetic Media expertise (AMT 2001), the ?rst convention of its variety, taking pictures the country of analysis and improvement in AMT and the most recent architectures, prototypes, instruments, and ?elded platforms that reveal or permit AMT. the quantity is geared up into the subsequent 8 elements: I. shrewdpermanent electronic - dia; II. internet Personalization; III. lively Interfaces; IV. self sustaining Agent - proaches; V. Facial photo Processing; VI. AMT-Supported trade, enterprise, studying, and wellbeing and fitness Care; VII. instruments and strategies; and VIII. Algorithms.
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Extra resources for Active Media Technology: 6th International Computer Science Conference, AMT 2001 Hong Kong, China, December 18–20, 2001 Proceedings
4. Time series of k of the power spectrum inclination angle of the traﬃc of Fig. 2A 4 Discussion In the recent works of 1/f ﬂuctuation at DFT analysis of the Internet and simulation of the theoretical network, that is the point of k=−1 in this research, 1/f ﬂuctuation of the power spectrum of the network traﬃc appear at critical region of capability of the network. From result of the experiment and recent works, the relation between the working state of the network and k of the power spectrum inclination angle is displayed in Table 1.
As a result, it is better to apply only the suitable techniques for each application. In this section, recent personalization techniques are classified and then studied. This study classifies personalization systems into two main categories: customer-driven personalization and business-driven personalization systems (Luedi, 1997; Levin, 1999). Figure 1 displays a classification of personalization techniques. 1 Customer-Driven Systems Customer-driven personalization systems allow customers to visit a site faster and more effectively.
Time series of the network transmission time and the power spectrum; at the I and II region of Fig. 2 where, fn = n N N , n = − , · · · , , hk = h(k∆), N∆ 2 2 Congestion Prospect of Network Traﬃcs by Fluctuation 21 N is the number of sampling data, ∆ is the sampling time, and hk is the sampling data. 57 (Fig. 3B). 18 (Fig. 3D). The k of the power spectrum inclination is calculated by least-squares method built into M AT HEM AT ICA. The some relation between the traﬃc and k of the power spectrum inclination angle is anticipated from Fig.
Active Media Technology: 6th International Computer Science Conference, AMT 2001 Hong Kong, China, December 18–20, 2001 Proceedings by Toshio Fukuda (auth.), Jiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida (eds.)