in the last two decade the use of aerial laser scanner (als) or lidar (light detection and ranging) sensor in geomatics engineering and surveying application has augmented significantly . the main reason of the mentioned phenomenon is the reliability and accuracy of the data obtained by lidar sensors. the output of lidar is unclassified 3d point cloud. classification of the lidar point clouds i...

Genetic fuzzy rule selection has been successfully used to design accurate and compact fuzzy rulebased classifiers. It is, however, very difficult to handle large data sets due to the increase in computational costs. This paper proposes a simple but effective idea to improve the scalability of genetic fuzzy rule selection to large data sets. Our idea is based on its parallel distributed impleme...

This paper presents a new approach to fuzzy rulebased modeling of nonlinear systems from numerical data. The novelty of the approach lies in the way of input partitioning and in the syntax of the rules. This paper introduces interpretable relational antecedents that incorporate local linear interactions between the input variables into the inference process. This modification improves the appro...

We describe the design of privacy controls and feedback mechanisms for contextual IM, an instant messaging service for disclosing contextual information. We tested our designs on IMBuddy, a contextual IM service we developed that discloses contextual information, including interruptibility, location, and the current window in focus (a proxy for the current task). We deployed our initial design ...

We introduce a new programming language called INI, which eases the development of self-adaptive software. INI combines both rulebased and event-based programming paradigms, by allowing the definitions of rules that can be triggered by events. Besides a convenient language-level support for synchronization, the key point with INI events is that they come with a configuration layer, which is set...

This paper presents a method to incorporate statistical information into a rulebased parser to resolve syntactic ambiguities. We extract the statistical information from the Penn Treebank, and apply the information to the rule-based parser. For the extraction of the statistical information the tag conversion is needed because of the disagreement of the tags and the bracketing style. We will sho...

Statistical approaches have recently emerged as the main paradigm in Machine Translation (MT) research. In previous work we have shown that results of a simple statistical word-based MT system may be highly comparable to those produced by a rule-based approach for closely-related languages such as Brazilian Portuguese and European Spanish. In this work we take the discussion one step further an...

We have developed two conceptually different systems that are able to identify named entities from spoken audio. One (referred to as SPRACH-S) has a stochastic finite state machine structure for use with an acoustic model that identifies both words and named entities from speech data. The other (referred to as SPRACH-R) is a rulebased system which uses matching against stored name lists, partof...

A self-organizing incremental learning model that attempts to combine inductive learning with prior knowledge and default reasoning is described. The inductive learning scheme accounts for useful generalizations and dynamic priority allocation, and effectively supplements prior knowledge. New rules may be created and existing rules modified, thus allowing the system to evolve over time. By comb...