This paper focuses on age-related change in sleep and improves our sleep estimation method by employing the feature of such relation between sleep stage and age. In particular, the wake stage increases as the age increases, while Non-REM stage decrease as the age increase. Using such distinctive features, we propose a new determination sleep stages, and introduce it into for our sleep estimation method based on Genetic Algorithms (GAs), which evolve the sleep stage for each person according to the fitness. To investigate an effectiveness of a new determination of sleep stages, we compare the estimated sleep stages of our method employing the proposed fitness function with that of Hirose’s method. The experimental results suggest that our method employed the proposed discretization of sleep stages has a capability to estimate the sleep stage accurately than Hirose’s method.

We are conducting a project to build a knowledge infrastructure to improve common understandings and knowledge among doctors, patients and researchers. The knowledge infrastructure consists of terms and semantic relationships among them, represented using the hypernetwork model. In order to build a merged knowledge representation, the terms used by the patients and doctors/researchers were analyzed. Less than fifth of terms were common, indicating differences in viewpoints.

This paper introduces the ongoing MyFinder project, which was launched in October 2010. The goals of this project are: (1) to propose an intimate personal genome information environment, MyFinder, which supports the search for our inborn talents and maximizes our potential for a meaningful life; and (2) to contribute to scientific discoveries in the biomedical or psychological research domains through intelligent community computing, or in other words, citizen science. This paper describes our research framework and the ongoing challenges to achieving these two goals. We also discuss the technical and social issues related to possible personal genome applications in non-medical domains.

A need for sleep monitoring is increasing in modern society. However, sleep stage scoring is time consuming, and large inconsistencies may exist among scorers. The settings for the recordings are also complicated and usually need to be professionally prepared. If simple small equipment could record human EEG and detect sleep stages, it would bring significant benefits to a large population. We thus developed a simple frequency-based sleep stage classifier by single EEG derivation, and evaluated the performance of the classifier. It showed a potential to work as well as the other known automated classifiers. The classifier was not based on specific frequency bands or EEG patterns. It could perform as well with poor quality signals and could easily be adopted to score any other biological signals.

Although web-based information extraction systems draw much attention, most of such systems assume that the web directly reflects the real world. For instance, Google flu trend, which is one of the-state-of-the-art influenza surveillance systems, relies on the basic idea that the amount of the influenza related search queries directly correlates with the number of the influenza patients. However, the real patients suffering from influenza symptoms are invisible in the web, because they do not use Internet. Considering this gap, this paper employs an infectious model, assuming that a potential patient utilizes Internet at the first sign of flu. The proposed model improves two types of the state-of-the-art systems, Google based system (from 0.837 correlation to 0.928) and Twitter based system (from 0.898 correlation to 0.918). This study demonstrated that a simple model could easily improve the web-based surveillance.

This paper proposes a novel telemedicine system for type 2 diabetes patients. The proposed system supports the patient self-management via a set of telemedicine devices, consisting of health sensors and a smart phone. The proposed system covers not only the sensor data but also the diet (food) and exercise data. To capture the food information, we also developed the voice recognition module focusing on the food names. The basic feasibility of the system is practically demonstrated in the preliminary experiment.

The concept of trust in web services describes the degree of belief that a client or a group of clients have over services functioning satisfactorily and providing the expected results. As services are usually invoked in composition with other services, judging on their trustworthiness gets more complicated, yet computing their trustworthy becomes a desired goal. Existing work only take the trust of each individual service into account, regardless of the context of the composition. They also do not use the data gained from other clients for selecting the most trustful composition and preparing for possible service failures. In our work we first introduce the concept of Combination Reputation, which reflects the commonness and popularity of invoaction of a pair or group of services among other clients. By interpreting the trust and reputation values as subjective probability, we define the Component Trust of the services in the composition, which reflects the degree of belief the client has over components of services performing satisfactorily. We model the web service composition as a Bayesian network and integrate the above trust values into the network and show how to compute the global trust of the composition.

Service composition, which achieves the goal of value-added services, has been considered as the core technique of Service-oriented Computing (SOC). To cope with the challenge of ever-increasing number of web services, graph-based web service network has emerged as a potential solution to the state of art SOC. In such a way, composite services are constructed by applying searching algorithms to the built graph, and proved to achieve outstanding performance in complexity. However, web service network suffers two crucial disadvantages: poor connectivity and negative links, and both of them have crucial negative impact on service composition. To cope with the problems, we propose two methods in this paper. Firstly, leveraging social network analysis, we focus on enriching web service network by adding valuable services, which will play positive roles in solving poor connective problem. Secondly, we show a serious status that numerous negative links contained in the underlying networks, and then we propose to identify and remove the negative links based on users’ historical composite services.

A number of real-world security scenarios can be cast as a problem of transiting an area guarded by a mobile patroller, where the transiting agent aims to choose its route so as to minimize the probability of encountering the patrolling agent, and vice versa. We model this problem as a two-player zero-sum game on a graph, termed the transit game. In contrast to the existing models of area transit, where one of the players is stationary, we assume both players are mobile. We also explicitly model the limited endurance of the patroller and the notion of a base to which the patroller has to repeatedly return. Noting the prohibitive size of the strategy spaces of both players, we develop single- and double-oracle based algorithms including a novel acceleration scheme, to obtain optimum route selection strategies for both players. We evaluate the developed approach on a range of transit game instances inspired by real-world security problems in the urban and naval security domains.

In all of these problems, we have limited with researchers in other disciplines, be "on the ground" security resources which prevent full security coverage with domain experts, and examine real-world constraints at all times; instead, limited security resources must be deployed and challenges that cannot be abstracted away. Together as intelligently taking into account differences in priorities an international community of multiagent researchers, we of targets requiring security coverage, the responses of can accomplish more! the adversaries to the security posture and potential uncertainty over the types, capabilities, knowledge and priorities