Analysing imperfect temporal information in GIS using the Triangular Model

Rough set and fuzzy set are two frequently used approaches for modelling and reasoning about imperfect time intervals. In this paper, we focus on imperfect time intervals that can be modelled by rough sets and use an innovative graphic model [i.e. the triangular model (TM)] to represent this kind of imperfect time intervals. This work shows that TM is potentially advantageous in visualizing and querying imperfect time intervals, and its analytical power can be better exploited when it is implemented in a computer application with graphical user interfaces and interactive functions. Moreover, a probabilistic framework is proposed to handle the uncertainty issues in temporal queries. We use a case study to illustrate how the unique insights gained by TM can assist a geographical information system for exploratory spatio-temporal analysis

Integrity Control in Relational Database Systems - An Overview

This paper gives an overview of research regarding integrity control or integrity constraint handling in relational database management systems. The topic of constraint handling is discussed from two points of view. First, constraint handling is discussed by identifying a number of important research issues, and by treating each issue in detail. Second, a number of projects is described that have resulted in the realization of database management systems supporting integrity constraints; the various projects are compared with respect to a number of system characteristics. Together, both approaches give a broad overview of the state of the art in the field at this moment

Determining a Patient Recovery from a Total Knee Replacement Using Fuzzy Logic and Active Databases

The purpose of the knowledge-based system is to predict the rehabilitation timeline of a patient in physical therapy for a total knee replacement. All patients have various attributes that contribute to their rehabilitation rate such as: weight, gender, smoking habit, medications, physical ability, or other medical problems. A combination of any one or several of these attributes will affect the recovery process. The proposed FRTP (Fuzzy Rehabilitation Timeline Predictor) is a fuzzy data mining model that can predict the recovery length of a patient in physical therapy for a total knee replacement and provide feedback to experts for revision of the physical therapy plans to meet the recovery goal. Using the FRTP, an approximate timeline for a patient can be predicted, thus creating more insight into the healing process. The process of analyzing patient data, predicting the number of weeks for the maximum healing result, adaptation of a different recovery plan based on our research prototype using fuzzy logic in database systems to maximize the recovery period, is a very interesting and important component for the patient, health insurance companies, medical clinics, and physicians. This research paper presents a methodology to analyze and mine the data using a web based application (Web Fuzzy Data Mining) and fuzzy calculus to perform data mining and predicting the best possible plan for a faster recovery

Cultural dialects of real and synthetic emotional facial expressions

In this article we discuss the aspects of designing facial expressions for virtual humans (VHs) with a specific culture. First we explore the notion of cultures and its relevance for applications with a VH. Then we give a general scheme of designing emotional facial expressions, and identify the stages where a human is involved, either as a real person with some specific role, or as a VH displaying facial expressions. We discuss how the display and the emotional meaning of facial expressions may be measured in objective ways, and how the culture of displayers and the judges may influence the process of analyzing human facial expressions and evaluating synthesized ones. We review psychological experiments on cross-cultural perception of emotional facial expressions. By identifying the culturally critical issues of data collection and interpretation with both real and VHs, we aim at providing a methodological reference and inspiration for further research

Neurons and symbols: a manifesto

We discuss the purpose of neural-symbolic integration including its principles, mechanisms and applications. We outline a cognitive computational model for neural-symbolic integration, position the model in the broader context of multi-agent systems, machine learning and automated reasoning, and list some of the challenges for the area of neural-symbolic computation to achieve the promise of effective integration of robust learning and expressive reasoning under uncertainty

Exploring sensor data management

The increasing availability of cheap, small, low-power sensor hardware and the ubiquity of wired and wireless networks has led to the prediction that `smart evironments' will emerge in the near future. The sensors in these environments collect detailed information about the situation people are in, which is used to enhance information-processing applications that are present on their mobile and `ambient' devices.\ud \ud Bridging the gap between sensor data and application information poses new requirements to data management. This report discusses what these requirements are and documents ongoing research that explores ways of thinking about data management suited to these new requirements: a more sophisticated control flow model, data models that incorporate time, and ways to deal with the uncertainty in sensor data