Myung-Eun Lim

A Smart Medication Prompting System and Context Reasoning in Home Environments

This paper is concerned about a medication reminding service in home environments and its context reasoning method to recognize the service suitable for medication situation. To provide an appropriate medication service depending on the users situation, it is needed to model and infer the context based on users condition. In this paper, we proposed a method to organizing the context model and a reasoning engine to infer the service. We used jess rule engine to build our reasoning engine and suggested a context resolving method to avoid conflict caused by similar invoke conditions.

Proactive medication assistances based on spatiotemporal context awareness of aged persons

In this paper, we developed a system that could assist appropriate activities for medication adherence of the elderly. It employs a proactive knowledge which is represented as templates predefined for their medication activities. The knowledge-based assistance depends on the contexts considerably, which the system can recognize by continuously monitoring the current position and the time-schedule for their medications. The monitoring is performed with ultrasonic sensors and infrared sensors mounted in a display and a pillbox mainly. According to the recognized contexts, the medication activities can he serviced through old person-friendly multimedia display. In special, since the knowledge is well-defined by XML, only its content modification can provide a variety of services individually customized to the elderly.

An Adaptive Recommendation System with a Coordinator Agent

This paper presents a recommendation system with a coordinator agent that is adaptive to its environment. Recommendation systems that suggest items to users are gaining popularity in the field of electronic commerce. Various methods such as collaborative, content-based, and demographic recommendation have been used to analyze and predict the preference of users. According to the characteristic of the application domain, the performance of each method varies. In the proposed system, we introduce a coordinator agent that adaptively changes the weights of each recommendation method to provide combined recommendation appropriate for the given environment.

Distance correction system for localization based on linear regression and smoothing in ambient intelligence display

This paper suggests the method of correcting distance between an ambient intelligence display and a user based on linear regression and smoothing method, by which distance information of a user who approaches to the display can he accurately output even in an unanticipated condition using a passive infrared VIR) sensor and an ultrasonic device. The developed system consists of an ambient intelligence display and an ultrasonic transmitter, and a sensor gateway. Each module communicates with each other through RF (Radio frequency) communication. The ambient intelligence display includes an ultrasonic receiver and a PIR sensor for motion detection. In particular, this system selects and processes algorithms such as smoothing or linear regression for current input data processing dynamically through judgment process that is determined using the previous reliable data stored in a queue. In addition, we implemented GUI software with JAVA for real time location tracking and an ambient intelligence display.

Mobile personal sports activity management app

In order to expect the effect of promotion of health through the activation of personal sports activity, scientific data management based on quantification of personal sports activity is needed. However there is a lack of integrated management systems of various sport activities as well as motivating factor for ongoing participation in sports activity. This paper proposes an effective integration and management method of the personal sports activity data. The data can be used for the certification of personal sports activity for personal use in the future. The personal sports activity management system has developed with mobile app.

Design of a context-aware model to enhance medication adherence

Medication adherence is important to patients who suffer from chronic disease. Regular medication activity reduces the cost of caring disease and prohibits the worsening of disease condition. To support patients taking medicine correctly, we developed a medication assistance system which alarms medication situation through multimedia messages and help patients to take a medicine. To enable the system copes with various situations related to a medication service, we designed a medication context model and implemented a state based context aware application. We also applied our system to patients and saw a little improvement in medication adherence.

Design of a description language for generating wrapper to collect biological data

The biological data are scattered in various areas with various formats and they are changing continuously. Therefore, data integration becomes an important issue to provide researcher a dynamic access of data. In the data integration process, the method of extracting heterogeneous data dynamically from the data source is an essential part. Data extraction method using wrapper can provide flexibility and extensibility to an integration system.

Improving Rule Generation Precision for Domain Knowledge based Wrappers

Wrappers play an important role in extracting specified information from various sources. Wrapper rules by which information is extracted are often created from the domain-specific knowledge. Domain-specific knowledge helps recognizing the meaning the text representing various entities and values and detecting their formats. However, such domain knowledge becomes powerless when value-representing data are not labeled with appropriate textual descriptions or there is nothing but a hyper link when certain text labels or values are expected. In order to alleviate these problems, we propose a probabilistic method for recognizing the entity type, i.e. generating wrapper rules, when there is no label associated with value-representing text. In addition, we have devised a method for using the information reachable by following hyperlinks when textual data are not immediately available on the target Web page. Our experimental work shows that the proposed methods help increasing precision of the resulting wrapper, particularly extracting the title information, the most important entity on a Web page. The proposed methods can be useful in making a more efficient and correct information extraction system for various sources of information without user intervention

An integrated system of mining HTML texts and filtering structured documents

This paper presents a method of mining HTML documents into structured documents and of filtering structured documents by using both slot weighting and token weighting. The goal of a mining algorithm is to find slot-token patterns in HTML documents. In order to express user interests in structured document filtering, slot and token are considered. Our preference computation algorithm applies vector similarity and Bayesian probability to filter structured documents. The experimental results show that it is important to consider hyperlinking and unlablelling in mining HTML texts; slot and token weighting can enhance the performance of structured document filtering.