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5 6, pp 575 584 Ozawa, S, S Pang, N Kasabov (2008) Incremental Learning of Chunk Data for On-line Pattern Classi cation Systems, IEEE Trans on Neural Networks, Vol 19, No 6, pp 1061 1074 Pang, S, S Ozawa, N Kasabov (2005) Incremental Linear Discriminant Analysis for Classi cation of Data Streams IEEE Trans on Systems, Man, and Cybernetics, Part B, Vol 35, No 5, pp 905 914 Sanger, T D (1989) Optimal Unsupervised Learning in a Single-layer Linear Feedforward Neural Network, Neural Networks, Vol 2, No 6, pp 459 473 Scholkopf, B, A Smola, K-R Muller (1996) Nonlinear Component Analysis as a Kernel Eigenvalue Problem, MPI Technical Report, No 44 Shilton, A, M Palaniswami, D Ralph, A C Tsoi (2005) Incremental Training of Support Vector Machines IEEE Trans on Neural Networks, Vol 16, No 1, pp 114 131 Takeuchi, Y, S Ozawa, S.

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Abe (2007) An Ef cient Incremental Kernel Principal Component Analysis for Online Feature Selection Proc Int Joint Conf on Neural Networks 2007, CDROM Thrun S, L Pratt (1998) Learning to Learn Kluwer Academic Publishers, Boston, MA, USA Utgoff, P E (1989) Incremental Induction of Decision Trees, Machine Learning, Vol 4, No 2, pp 161 186..

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input. The input of the controller is the difference between the actual sample and the interpolated value. If the interpolation is smaller than the sample, its slope is increased, otherwise it is decreased. The main advantage of the PLL-based approach is that it requires far less memory than the linear-regression technique (in essence only the current state of the integrator sum). The main disadvantage is that PLLs require a long convergence time to achieve a stable rate [17]. The NTP algorithm uses a PLL [18]. 7.4.4 Combining Multiple Time Intervals

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Note. The asterisk indicates membership in the statistically equivalent superior group. (L) indicates that the procedure performed signi cantly worse than the other methods.

Identifying AT, 397, 420 Identifying RT, 398, 401, 420

disease (COPD), the results are relevant because inhaled medications are a cornerstone of COPD treatment, as they are for asthma. It appears, then, that the presence of an intimate partner and satisfaction with close relationships may be associated with more appropriate medication utilization (more adherent use of medications; less necessity for oral steroids suggesting better disease control through inhaled medications), perhaps resulting in less morbidity due to asthma. As mentioned, patients with a tendency toward generalized fearful, catastrophizing reactions have more medical utilization. How might fearful reactions and social relationships interact in patients with asthma Two models are relevant: rst, the concept of the safety signal, which was developed based on persons with panic disorder. Safety signals are items (e.g., medications) or people associated with feelings of security and relief (Rachman, 1984). Among patients with asthma, the presence of the signi cant other may be hypothesized to decrease fearful cognitions, and be associated with lesser reports of asthma symptoms. An alternate hypothesis comes from kindling-sensitization models that posit that over time, increasingly lower levels of stimuli are needed to prompt the occurrence of the target symptoms (Post, Rubinow, & Ballenger, 1986). Extending this model to asthma, to the extent that the signi cant other is a source of stress, the signi cant other may be associated with increasing discomfort and greater reports of asthma symptoms over time. Theory-driven examinations of the role of the signi cant other and the moderating effects of relationship satisfaction await future research efforts.

37 dBrnC 10(log X 10 9 ) 0.5 + 90 dB. 10(log X 10 9 ).

Compared with the NBT, the transmitter does not turn on the receiver to wait for a beacon. Thus, the energy consumption for transmitting activity is derived from (18.10) and energy consumption for transmission without tracking overhead is derived from the following: ETX 2 rtWI tminB r max tminB ; tBC E tTUD tWI 18:11

420 A P P L I C A T I O N S O F E V O L V I N G I N T E L L I G E N T S Y S T E M S T O O I L A N D G A S I N D U S T R Y

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