Item recommendation based on context-aware model for personalized u-healthcare service

A personalized service in the ubiquitous environment is to provide services or items, which reflect personal tastes, attitudes, and contexts. It is impossible to reflect the context information generated in u-healthcare environments due to the existing recommendation system performing the recommendation using the information directly input by users and application usage record only. This study develops a context-aware model using the context information provided by the context information model. The study applies it to the extraction of the missing value in a collaborative filtering process. The context-aware model reflects the information that selects items by users according to the appropriate context using the C-HMM and provides it to users. The solution of the missing value in the preference significantly affects the recommendation accuracy in a preference based item supply method. Thus, this study developed a new collaborative filtering for ubiquitous environments by reflecting the missing preference value and reflecting it to the collaborative filtering using the context-aware model. Also, the validity of this method will be evaluated by applying it to menu services in u-healthcare services.     

Multiple categorizations of products: cognitive modeling of customers through social media data mining

As various forms of social media are spreading, we often witness that an idea of an individual user drives macroscopic changes. From the perspectives of product development and marketing, the opinions left by potential consumers in online social network can generate big ripple effects. This study analyzes the user opinions in online space to grasp preferences toward various products psychologically categorized by users. We also suggest an aspect of the market mentally configured by users using network modeling while following the framework of economic sociology. Existing analyses on online market place are mainly dealing with structural issues such as inter-actor relationships and status measurement. This study, however, analyzes complex preferences regarding diverse products and brands and derives a new model for inter-market connections. We expect that our study will provide important consequences on digital marketing and community design of corporations planning word of mouth effect in online space.     

Development of head detection and tracking systems for visual surveillance

This paper proposes a technique for the detection of head nod and shake gestures based on eye tracking and head motion decision. The eye tracking step is divided into face detection and eye location. Here, we apply a motion segmentation algorithm that examines differences in moving people’s faces. This system utilizes a Hidden Markov Model-based head detection module that carries out complete detection in the input images, followed by the eye tracking module that refines the search based on a candidate list provided by the preprocessing module. The novelty of this paper is derived from differences in real-time input images, preprocessing to remove noises (morphological operators and so on), detecting edge lines and restoration, finding the face area, and cutting the head candidate. Moreover, we adopt a K-means algorithm for finding the head region. Real-time eye tracking extracts the location of eyes from the detected face region and is performed at close to a pair of eyes. After eye tracking, the coordinates of the detected eyes are transformed into a normalized vector of x-coordinate and y-coordinate. Head nod and shake detector uses three hidden Markov models (HMMs). HMM representation of the head detection can estimate the underlying HMM states from a sequence of face images. Head nod and shake can be detected by three HMMs that are adapted by a directional vector. The directional vector represents the direction of the head movement. The vector is HMMs for determining neutral as well as head nod and shake. These techniques are implemented on images, and notable success is notified.     

Efficient Algorithms for Computing a Complete Visibility Region in Three-Dimensional Space

Given a set P of polygons in three-dimensional space, two points p and q are said to be visible from each other with respect to P if the line segment joining them does not intersect any polygon in P . A point p is said to be completely visible from an area source S if p is visible from every point in S . The completely visible region CV(S, P) from S with respect to P is defined as the set of all points in three-dimensional space that are completely visible from S . We present two algorithms for computing CV(S, P) for P with a total of n vertices and a convex polygonal source S with m vertices. Our first result is a divide-and-conquer algorithm which runs in O(m ² n ² α(mn)) time and space, where α(mn) is the inverse of Ackermann's function. We next give an incremental algorithm for computing CV(S,P) in O(m ² n+mn ² α(n)) time and O(mn+n ² ) space. We also prove that CV(S,P) consists of Θ(mn+n ² ) surface elements such as vertices, edges, and faces. Received November 16, 1995; revised November 11, 1996.     

Linear-Time Algorithms for Finding the Shadow Volumes from a Convex Area Light Source

An area light source in three-dimensional space shines past a scene polygon to generate two types of shadow volumes for each scene polygon, i.e., one with partial occlusion and the other with complete occlusion. These are called penumbra and umbra, respectively. In this paper we propose linear-time algorithms for computing the penumbra and the umbra of a scene polygon from an area light source, respectively. Received June 27, 1995; revised May 20, 1996.     

Characterizing and recognizing the visibility graph of a funnel-shaped polygon

A funnel, which is notable for its fundamental role in visibility algorithms, is defined as a polygon that has exactly three convex vertices, two of which are connected by a boundary edge. In this paper we investigate the visibility graph of a funnel which we call an F-graph.We first present two characterizations of an F-graph, one of whose sufficiency proof itself is a linear time Real RAM algorithm for drawing a funnel on the plane that corresponds to an F-graph. We next give a linear-time algorithm for recognizing an F-graph. When the algorithm recognizes an F-graph, it also reports one of the Hamiltonian cycles defining the boundary of its corresponding funnel. This recognition algorithm takes linear time even on a RAM.We finally show that an F-graph is weakly triangulated and therefore perfect, which agrees with the fact that perfect graphs are related to geometric structures.This work was supported in part by the Korea Science and Engineering Foundation under Grant 91-01-01.     

Home Health Gateway Based Healthcare Services Through U-Health Platform

The Ubiquitous Health, or u-Health, service is an IT health care service using the ubiquitous computing environment. U-Health provides customized medical services. As it is a service that has developed from the current hospital visiting medical system, the u-Health service provides a patient with healthcare anywhere and anytime. In this paper, we propose a home health gateway based healthcare services through the u-Health platform. Using home health gateway, u-Health can provide health monitoring, diet, and exercise services using the healthcare decision support module in the ubiquitous environment. This approach would offer specialized services using an external content provider of DB. In addition, a doctor can provide advice to patients using the monitoring service. The proposed u-Health platform provides effective services using home health gateway in ubiquitous environments to customers, which will improve the health of chronic patients.     

Single tag sharing scheme for multiple-object RFID applications

RFID systems have been widely adopted in various industrial as well as personal applications. However, traditional RFID systems are limited to address only one tag for each application object. This limitation hinders the usability of RFID applications because it is difficult, if not impossible, to distinguish many tags simultaneously with existing RFID systems. In this paper, we propose a new RFID tag structure to support multiple-objects that can be easily shared by many different RFID applications. That is, the proposed RFID tag structure supports that a tag maintains several different objects and allows those applications to access them simultaneously. We also propose an authentication protocol to support multiple-object RFID applications. Especially, we focus on the efficiency of the authentication protocol by considering different security levels in RFID applications. The proposed protocol includes two types of authentication procedures. In the proposed protocol, an object has its security level and goes through one of different authentication procedures suitable for its security level. We report the results of a simulation to test the performance of the proposed scheme. In our simulation, we considered the safety of our scheme against potential attacks and evaluated the efficiency of the proposed protocol.