In this paper, we propose a method to extract features from three-dimensional acceleration signals. The proposed method is based on the (auto-)correlation matrix of Fourier transform features, naturally containing the correlations between the frequencies as well as the ordinary power spectrum for each frequency. The proposed features are inherently invariant to both rotational variations and temporal shift (delay), whereas the other methods employ ad hoc preprocessing to increase robustness to those variations. Thereby, we can favorably apply the proposed method to analyze 3-D acceleration signals regardless of the orientations of the accelerometer. In the experiment on gait identification using an accelerometer embedded in a cellular phone, the proposed method outperformed the other methods.

The questions of how to represent passbacks (redoing) of work in a workflow and of what semantics to apply to passbacks comprise an important issue in workflow research. In this paper, cyclic workflows are regarded as workflows with passbacks, and the normal form of a workflow is defined from properties of workflows as graphs. For a normal workflow, semantics based on passbacks is defined as a transition system on subgraphs of the workflow. Based on the transition system, this paper defines total correctness of a workflow with passbacks. Furthermore, this paper proves that total correctness of workflows with passbacks, defined in this paper, is a natural extension of the conventional correctness of acyclic workflows. This paper also shows that the correctness of a normal workflow amounts to the correctness of the acyclic sub-workflows included in the normal workflow.

This paper describes a methodology that providers of services can use to adapt their software applications, both intra-net and inter-net systems, to the changes of their business environment. The methodology enables agile software development based on a Web process architecture that executes ontology-based business processes as workflow systems. Ontology construction technology is used to extract business model of tasks and processes from business documents, model them, and organize them. Reflective semantics interoperates between RDF/XML representation of business tasks and Java objects of business process primitives. The gap between business models and service system applications is bridged by a Java-based software framework that executes business process as a set of Web page transitions. As a result, a business model is implemented as a thin client application. The software framework enables rapid spiral development of short-term cycles because business modelers, software developers, and users are able to share the same framework of description and systems. The feasibility of the methodology described here has been demonstrated in projects developing local-government workflow systems.

Usability is a vital quality factor of electronic environments. Increasing complexity of Web based platforms and mining large data volumes constantly rise demands on effective usability analysis tools. The article presents a novel formalism allowing examination of usability characteristics with the spectrum of metrics. The approach was applied to the usability analysis of a large corporate intranet. Majority of the users were knowledge workers. Important usability features have been revealed. The knowledge workers efficiently utilized only a minor portion of available intranet resources and exhibited strong pattern formation tendency. The frequently repeating browsing patterns were generally easily executable

Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called POLYPHONET, which employs several advanced techniques to extract relations of persons, detect groups of persons, and obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents.Several studies have used search engines to extract social networks from the Web, but our research advances the following points: First, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social networking mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Super Social Network Mining is proposed; it utilizes simple modules using Google and is characterized by scalability and Relate-Identify processes: Identification of each entity and extraction of relations are repeated to obtain a more precise social network.

In a ubiquitous computing environment, it is desirable to provide a user with information depending on a user's situation, such as time, location, user behavior, and social context. At conventions, such as academic conferences and exhibitions, where participants must register in advance, the social context of participants can be extracted from the Web using their names and affiliations without asking the participants many questions. Here, we attempt to extract the social network of participants from the Web, where a node represents a participant and an edge represents the relationship of two participants. Each edge is added using the number of pages retrieved by a search engine which include both participants names. Moreover, each edge has a label such as "coauthors" and "members of the same project" by applying classification rules to the page content. We show an example of the extracted network and make a preliminary evaluation. This network can be used in many information services, such as finding an appropriate introducer or negotiator, and who one should talk to in order to efficiently expand his/her network.

In this paper, we present the tools standardized by MPEG-7 for describing the semantics of multimedia. In particular, we focus on the abstraction model, entities, attributes and relations of MPEG-7 semantic descriptions. MPEG-7 tools can describe the semantics of specific instances of multimedia such as one image or one video segment but can also generalize these descriptions either to multiple instances of multimedia or to a set of semantic descriptions. The key components of MPEG-7 semantic descriptions are semantic entities such as objects and events, attributes of these entities such as labels and properties, and, finally, relations of these entities such as an object being the patient of an event. The descriptive power and usability of these tools has been demonstrated in numerous experiments and applications, these make them key candidates to enable intelligent applications that deal with multimedia at human levels.