Abstract: Cell formation is the first step in the design of cellular
manufacturing systems. In this study, a general purpose
computational scheme employing a hybrid tabu search algorithm as
the core is proposed to solve the cell formation problem and its
variants. In the proposed scheme, great flexibilities are left to the
users. The core solution searching algorithm embedded in the scheme
can be easily changed to any other meta-heuristic algorithms, such as
the simulated annealing, genetic algorithm, etc., based on the
characteristics of the problems to be solved or the preferences the
users might have. In addition, several counters are designed to control
the timing of conducting intensified solution searching and diversified
solution searching strategies interactively.
Abstract: Hemodialysis patients might suffer from unhealthy
care behaviors or long-term dialysis treatments. Ultimately they need
to be hospitalized. If the hospitalization rate of a hemodialysis center
is high, its quality of service would be low. Therefore, how to decrease
hospitalization rate is a crucial problem for health care. In this study
we combined temporal abstraction with data mining techniques for
analyzing the dialysis patients' biochemical data to develop a decision
support system. The mined temporal patterns are helpful for clinicians
to predict hospitalization of hemodialysis patients and to suggest them
some treatments immediately to avoid hospitalization.