This study aimed to investigate the aspects of an individual's writing process that play important role in improving quality products, as well individual cognition on products. A factorial analysis design was used this study. The results study, first, spontaneous revision and vocabulary affect writing. In addition, it also found students with better reading ability tended do more intensive onli...

Periprosthetic joint infection (PJI) due to Salmonella is rare. It frequently occurs patients receiving immunosuppressive medicine. We describe two periprosthetic Salmonella infection of two immunocompromised patients. Both of patients were receiving azathioprine and prednisolone therapy. First patient presented six years after total hip arthroplasty with a huge abscess on her right thigh that ...

JALYN® (DUTASTERIDE/TAMSULOSIN): A NEW OPTION IN BPH n the U.S., the leading method of contraception is the combination oral contraceptive pill. More than 10 million women aged 15-44 years use the birth control pill as their primary method of contraception.1 Since the first BCP approval in 1960, the FDA has approved many oral contraceptive products. Most of these products use ethinyl estradiol ...

Multi-step forecasts can be produced recursively by iterating a one-step model, or directly using a specific model for each horizon. Choosing between these two strategies is not an easy task since it involves a trade-off between bias and estimation variance over the forecast horizon. Using a nonlinear machine learning model makes the tradeoff even more difficult. To address this issue, we propo...

Multi Agent Relational Action Learning considers a community of agents, each rationally acting following some relational action model. The observed effect of past actions that led an agent to revise its action model can be communicated, upon request, to another agent, speeding up its own revision. We present a framework for such collaborative relational action model revision.

We consider the problem of belief revision in a multi-agent system with information stemming from different agents with different degrees of credibility. In this context an agent has to carefully choose which information is to be accepted for revision in order to avoid believing in faulty and untrustworthy information. We propose a revision process combining selective revision, deductive argume...

We consider the problem of belief revision in a multi-agent system with information stemming from different agents with different degrees of credibility. In this context an agent has to carefully choose which information is to be accepted for revision in order to avoid believing in faulty and untrustworthy information. We propose a revision process combining selective revision, deductive argume...

While natural language as an interaction modality is increasingly being accepted by users, remaining technological challenges still hinder its widespread employment. Tools that better support the design, development and improvement of these types of applications are required. This demo presents a prototyping framework for Spoken Dialog System (SDS) design which combines existing language techno...

Multi-step forecasts can be produced recursively by iterating a one-step model, or directly using a specific model for each horizon. Choosing between these two strategies is not an easy task since it involves a trade-off between bias and estimation variance over the forecast horizon. Using a nonlinear machine learning model makes the tradeoff even more difficult. To address this issue, we propo...

We present two models of hierarchical structured multi-agents, and we describe how to obtain a modal knowledge base from distributed sources. We then propose a computationally oriented revision procedure for modal knowledge bases. This procedure is based on a labelled tableaux calculi supplemented with a formalism to record the dependencies of the formulae. The dependencies are then used to rec...