To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human–computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual caregiver system using mobile chatbot. Unlike the conventional health monitoring approach, our key idea is to integrate a rule-based virtual caregiver system (called “Mind Monitoring” service) with the physical, mental, and social questionnaires into the mobile chat application. The elderly person receives one question from the mobile chatbot per day, and answers it by pushing the optional button or using a speech recognition technique. Furthermore, a novel method is implemented to quantify the answers, generate visual graphs, and send the corresponding summaries or advice to the specific elder. In the experimental evaluation, we applied it to eight elderly subjects and 19 younger subjects within 14 months. As main results, its effects were significantly improved by the proposed method, including the above 80% in the response rate, the accurate reflection of their real lives from the responses, and high usefulness of the feedback messages with software quality requirements and evaluation. We also conducted interviews with subjects for health analysis and improvement.

To detect the theft of Java class files efficiently, we propose a concept of Java birthmarks, which are unique and native characteristics of every class file. For a pair of class files p and q, if q has the same birthmark as p's, q is suspected as a copy of p. Ideally, the birthmarks should satisfy the following properties: (a) preservation -- the birthmarks should be preserved even if the original class file is tampered with, and (b) distinction -- independent class files must be distinguished by completely different birthmarks. Taking (a) and (b) into account, we propose four types of birthmarks for Java class files. To show the effectiveness of the proposed birthmarks, we conduct three experiments. In the first experiment, we demonstrate that the proposed birthmarks are sufficiently robust against automatic program transformation (93.3876% of the birthmarks were preserved). The second experiment shows that the proposed birthmarks successfully distinguish non-copied files in a practical Java application (97.8005% of given class files were distinguished). In the third experiment, we exploit different Java compilers to confirm that the proposed Java birthmarks are core characteristics independent of compiler-specific issues.

This article presents a framework that adapts the conventional home electric appliances with the infrared remote controls (legacy appliances) to the emerging home network system (HNS). The proposed method extensively uses the concept of service-oriented architecture to improve programmatic interoperability among multi-vendor appliances. We first prepare APIs that assist a PC to send infrared signals to the appliances. We then aggregate the APIs within self-contained service components, so that each of the components achieves a logical feature independent of device/vendor-specific operations. The service components are finally exhibited to the HNS as Web services. As a result, the legacy appliances can be used as distributed components with open interfaces. To demonstrate the effectiveness, we implement an actual HNS and integrated services with multi-vendor legacy appliances.

In this paper, we present a new method to protect software against illegal acts of hacking. The key idea is to add a mechanism of self-modifying codes to the original program, so that the original program becomes hard to be analyzed. In the binary program obtained by the proposed method, the original code fragments we want to protect are camouflaged by dummy instructions. Then, the binary program autonomously restores the original code fragments within a certain period of execution, by replacing the dummy instructions with the original ones. Since the dummy instructions are completely different from the original ones, code hacking fails if the dummy instructions are read as they are. Moreover, the dummy instructions are scattered over the program, therefore, they are hard to be identified. As a result, the proposed method helps to construct highly invulnerable software without special hardware.

Many care robots have received a lot of attention to help elderly people, however existing care robots have difficult to adapt personalization. For instance, some programmers have to customize robot program to meet needs of individual. In this paper, the authors' goal is design and develop care robot which provides personalization for an individual elderly people with an efficient and reasonable way. Their proposed service consists of three essential components; VirtualCareGiver (VCG), VirtualCarePersonalizer (VCP) and CareTemplate. VCG is a robot agent, which provides a personalization and integration for each elderly people. The VCG is offered care tasks based on care template which VCP generates. VCP provides adaptation for individual elderly on the cloud. The authors also conduct an experimental evaluation to demonstrate the feasibility with actual 11 subjects in a day care center. As a result, both font size and voice volume are especially contributed for the subjects.

In the smart city environment, a wide variety of data are collected from sensors and devices to achieve value-added services. In this paper, we especially focus on data taken from smart houses in the smart city, and propose a platform, called Scallop4SC, that stores and processes the large-scale house data. The house data is classified into log data or configuration data. Since the amount of the log is extremely large, we introduce the Hadoop/MapReduce with a multi-node cluster. On top of this, we use HBase key-value store to manage heterogeneous log data in a schemaless manner. On the other hand, to manage the configuration data, we choose MySQL to process various queries to the house data efficiently. We propose practical data models of the log data and the configuration data on HBase and MySQL, respectively. We then show how Scallop4SC works as a efficient data platform for smart city services. We implement a prototype with 12 Linux servers. We conduct an experimental evaluation to calculate device-wise energy consumption, using actual house log recorded for one year in our smart house. Based on the result, we discuss the applicability of Scallop4SC to city-scale data processing.