Perceptions of elder abuse and help-seeking patterns among African-American, Caucasian American, and Korean-American elderly women

Thirteen scenarios were used to measure and compare the perceptions of elder abuse and help-seeking behaviors of African-American, Caucasian American, and Korean-American elderly women. Significant group differences existed in their perceptions of elder abuse with regard to six scenarios, and the Korean-American women were substantially less likely to perceive a given situation as abusive than the other groups. The three groups also showed significant differences in their intended use of formal and informal sources of help in the case of elder abuse.     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Congestion pricing of multi-modal transportation systems

This paper deals with the pricing and investment decision problem of multi-modal transportation systems in which the congestion is a significant factor in the assessment of system costs. This study approaches this congestion pricing problem with a number of social welfare maximization problems, all of which have the identical structure except financial constraints. One welfare maximization problem examined in this study yields the pricing and investment decision, which can attain the first-best social optimality for multi-modal transportation systems. Other welfare maximization problems show he second-best optimal solutions that can address two policy questions in transportation economics, namely, the cross-subsidy between competing modes and peak-period congestion charges on a single highway link. Received: February 2001/Accepted: December 2001 This work was supported in part by funds from BK21 Research Division of Seoul National University for Social Infrastructure and Construction Technology.     

On-line dead-time compensation method using disturbance observer

A new on-line dead-time compensation method for a permanent magnet (PM) synchronous motor drive is proposed. Using a simple disturbance observer without any additional circuit and off-line experimental measurement, disturbance voltages in the rotor reference dq frame caused by the dead time and nonideal switching characteristics of power devices are estimated in an on-line manner and fed to voltage references in order to compensate the dead-time effects. The proposed method is applied to a PM synchronous motor drive system and implemented by using software of a digital signal processor (DSP) TMS320C31. Simulations and experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed method.     

A unified group technology implementation using the backpropagation learning rule of neural networks

Two engineering problems in implementing Group Technology are part family formation and part classification. Regardless of the approach adopted for the formation and classification, a critical problem is how to maintain consistency. The consistency problem can be addressed most effectively if the formation and classification is a single procedure rather than two separate procedures. A feedforward neural network using the Backpropagation learning rule is adopted to automatically generate part families during the part classification process. The spontaneous generalization capability of the neural network is utilized in classifying the parts into the families and creating new families if necessary. A heuristic algorithm using the neural network is described with an illustrative example.     

A 0.8-V accurately tuned linear continuous-time filter

An accurately tuned low-voltage linear continuous-time filter is presented in this paper. Accurate tuning is achieved using time-constant matched master-slave tuning combined with power-up mismatch calibration. A low-pass biquad designed for a corner frequency of 115 kHz achieves better than -80-dB total harmonic distortion with a 250-mV/sub pp/ 10-kHz input signal. The prototype implemented in 0.18-/spl mu/m CMOS process occupies an area of 0.4 mm/sup 2/ and dissipates 4.6 mW (2.6 mW for the filter and 2 mW for tuning) of power.     

Effect of Annealing on the Surface Microstructure of Y-Ba-Cu-O Superconducting Ceramics

Precusors to the YBa₂Cu₃O_7-δ material were prepared by both the oxalate precipitation method and conventional ceramic processing. Second-phase grains were observed to develop on the exposed fracture surface during annealing at 500° to 600°C in an ambient atmosphere. The second-phase grains were identified to be BaCO₃ using EDX and XRD. The liquid phase, which was formed because of local chemical inhomogeneity in the Y-Ba-Cu-O system, contributed to the formation of second-phase grains as a source of Ba.