An important problem in the non-contractual marketing domain is discovering the customer lifetime and assessing the impact of customer's characteristic variables on the lifetime. Unfortunately, the conventional hierarchical Bayes model cannot discern the impact of customer's characteristic variables for each customer. To overcome this problem, we present a new survival model using a non-parametric Bayes paradigm with MCMC. The assumption of a conventional model, logarithm of purchase rate and dropout rate with linear regression, is extended to include our assumption of the Dirichlet Process Mixture of regression. The extension assumes that each customer belongs probabilistically to different mixtures of regression, thereby permitting us to estimate a different impact of customer characteristic variables for each customer. Our model creates several customer groups to mirror the structure of the target data set.

A cycling wheel chair (CWC) is a pedal-driven wheelchair developed as a personal transportation device for patients with hemiplegia after cerebral stroke. The CWC enables the patient to travel much faster than an ordinary wheel chair and is effective for prevention of disuse syndrome in lower limbs. However, the patients often have impairment of cognitive function as well as motor function. It is dangerous for such patients to ride on the CWC on outdoor roads. To cope with this problem, a virtual reality system for the CWC named “Virtual CWC” was developed. The Virtual CWC can provide safe and space-saving training and test environment for the patients. In the present study, a new scenario of the Virtual CWC has been developed to test the patient's cognitive function with respect to navigation as well as driving skills. The normal subjects' “homing vectors” obtained after riding on the Virtual CWC in three kinds of routes were analyzed, and compared between a young group (26 normal subjects; age 23.9 ± 2.5) and an elderly group (14 normal subjects; age 69.9 ± 4.1). As a result, the effect of cooperation between pedaling and steering could be found in the angular error of homing vectors in the case of the elderly group.

A six-layered architecture for behavior control, consciousness-based architecture (CBA), is developed to link symbolic behaviors to low-level behaviors such as reflex action, detour and pursuit. This architecture makes possible behaviors categorized in "use of media" in parallel with running low-level behaviors. Two emotion-valued criteria are given for vertical and horizontal behavior selection. While a level of behavior is chosen to maximize the consciousness intensity, a behavior at the level chosen is selected to increase the pleasure. In CBA, the obstruction of behavior triggers the elevation of the level of consciousness. Computer simulation successfully shows symbolic detour of an obstacle and enclosure of a prey by three creatures predicting the positions of mates, a prey and an obstacle. CBA also shows its advantage over a Q-learning technique for the obstacle detouring problem.