Money is enigmatic. Despite extensive investigation to date, conflicting theories persist regarding its nature. Examples include views that “Money is a physical object,” “Money is an abstract concept,” and “Money is institutional status,” among others. This paper aims to unravel this mystery by engaging in an ontological discourse on the essence of money and constructing a three-layer model that comprises (i) the representation (legitimacy) layer, (ii) the role layer, and (iii) the property layer. In the representation layer, official state-issued objects such as banknotes are examined through the lens of the representation theory. In the role layer, these objects act as monetary role holders, referred to as monetary objects, by playing the monetary role which is inherently social in nature. The three fundamental properties/functions of money—serving as a unit of economic value, being exchangeable with commodities, and capable of being stored—are inherent in monetary role, and hence in monetary objects. However, these properties/functions remain latent until they are possessed by agents. The property layer elucidates that money is a contingent property of the owner of monetary objects, who can engage in economic activities by harnessing/actualizing these three properties/functions. In summary, our ontological theory of money posits Money as a property, Monetary objects holding the Monetary role, whose player is the Legitimate representing thing issued by the authority. For instance, a freshly minted 20 Euro banknote is a legitimate representing thing, transitioning into a monetary object upon holding the monetary role within the economic context. Its institutional/causal power becomes operative upon ownership by an agent. Our theory adopts a monistic perspective rather than a dualistic one, facilitated by the above nuanced distinctions made among entities pertaining to “money.” Discussion about how our theory works for resolving some of the current issues is presented together with a justification for the observation that money virtually has use value in addition to exchange value.

In philosophy information is mainly discussed along with the notion of aboutness. In more practical communities, information is mainly addressed together with notions like data and knowledge. This paper proposes a different approach. We look at information (and related concepts) as roles played by representations. This view implies that the notion of representation is central for any ontological analysis of information and related concepts. The paper provides arguments for this new stand and discusses an ontological model of representation based on the systematic distinction between form and content. The broadness and flexibility of the proposed model is shown by discussing a list of variegated representation entities from music to procedure, from novel to painting. The paper also investigates the role of letters (characters) in natural language expressions, which turns out to be quite complex.

While working on ontology engineering for about 25 years, I think I unconsciously acquired my own methodology in ontology engineering. It is what I call ‘state-centric’ methodology. My background is in AI and Engineering rather than logic or philosophy, and it must have been driving me to understand reality in terms of states which are the heart of General Problem Solver (GPS). All my results on roles, functions, processes/events and causation (published in Applied Ontology) clearly show the utility of the state-centric methodology. My treatment of context seems rather unique since I claim that any object as a whole provides a context to its parts, and each of these play their assigned role to make the collection a unitary whole. The notion of ‘non-intentional goal’ together with the systemic context as its concretization works very well to capture temporal entities. The success of the unified definition of biological and artifact functions is largely based on this idea. The device ontology, which I have devised for enabling to capture dynamic and complex phenomena in a consistent manner, has been exploited in many of my works on function. It is a role assignment system and fully state-centric. In my recent work on causation, I have realized that any causation C → E can be mapped onto a function in which E is a non-intentional goal in the systemic context associated with C → E. The new functional talk of causation is fully state-centric which contrasts with the common idea that states should be excluded from the relata of causation. I found that the essence of causation exists in an occurrent in the form where State is the resultant state of the Event. In my keynote, I discuss the state-centric methodology through typical achievements on roles, function, processes/events and causation.

Persuasion profiling has been shown to be a promising method to personalize persuasive messages that can influence users. In the context of learning, persuade students towards following pedagogical tasks is an important role of teachers and intelligent educational environments. To accomplish persuasion, it is necessary to measure students' susceptibility to influence principles. Susceptibility to Persuasion Scale (STPS) is an instrument that can measure users' susceptibility to influence principles. Currently, STPS is validated only for the English language. Thus, this study presents the translation, cultural adaptation, and initial validation of the Brazilian Portuguese version of the STPS questionnaire. We probed into the validity and reliability of the resulting questionnaire with 582 participants. Our results indicate that the final version of our questionnaire, which contains 19-items and 6-components, has a reasonable internal consistence (Cronbach's alpha = 0.78) and can adequately identify which influence principles have more impact on user' decisions.

We introduce and formalize the key elements of a recent approach [1] to function definition that covers both biological and artefact functions. The paper concentrates on the steps from informal definitions to formal expressions and aims to show how to develop an ontological module for generic function representation. This part is done assuming the YAMATO ontology as background system. The second goal of the paper discusses how the module could be adapted to other foundational ontologies. In this part, we first point out the ontological assumptions on which the module relies and then discuss problems in reformulating them in other systems. This step is needed to verify whether and how the function module can be meaningfully used in other ontologies. We exemplify this case by discussing BFO and DOLCE, and by formalizing the module in the latter ontology.

We have built an instructional design support system called “FIMA-Light” which uncovers teacher’s intentions from his/her lesson plan and automatically visualizes them as goal decomposition trees. A decomposition tree expresses the ways of achieving a learner’s state change that should be realized in a whole lesson in the form of a tree structure. We have made use of FIMA-Light so that incumbent teachers themselves can improve their lessons. In this paper, we report on a practical use of goal-decomposition trees produced by FIMA-Light to improve trainee teachers’ skills in designing instructions before teaching practices in the teacher education program, and we discuss its effectiveness.

We believe that Culture can affect teaching and learning, primarily due to the existence of cultural variables in educational practices. The multiplication of opportunities to learn and teach abroad and the growing desire on the part of universities to attract an international clientele increase the need for cultural adaptation. However, as pointed out by Rogers, Graham and Mayes (2007), teachers are not always aware of these cultural variables. If these cultural variables were made explicit, it would be easier for instructional designers, teachers and learners to adapt to the different cultures. In this article, we present our understanding of the notion of Culture and an upper ontology of Culture modeled according to a procedural approach. We believe that such an approach allows us to make explicit the functionalities of Culture so that we are able to understand how it can influence not only our daily lives, but more particularly teaching and learning. It opens the door to concrete and practical solutions for cultural adaptation in ITSs.

Interactive Geometry software (IGS) are tools that help students to explore geometry concepts using computers. Most of IGS interfaces developed to date are heavily based on the desktop model of user interaction where the user input comes from the selection of icons and drop-down menus with the help of a mouse and a keyboard. Nevertheless, with the widespread adoption of smartphones, tablets and other devices with multitouch screens the tradition interfaces of IGS became inadequate. Thus, this study presents the development of a dictionary of gestures for interacting with IGS. It completely removes the need of icons and drop-down menus to create and manipulate geometric objects. To evaluate these gestures we implement them in an IGS for mobile device called Geotouch. Then, we conducted a usability study with five experts to compare Geotouch with other three IGS currently available. The results indicate that Geotouch has less usability problems and enable to build geometric objects faster and with fewer errors.

We present a model of Newtonian forces and the causal relations they are involved in, applying Röhl & Jansen's model of disposition (extended with a relation between dispositions and their existential conditions), and show that this model fits with the intuition that force is the result of an interaction. We formalize forces as dispositions, dissociating field forces (which have local fields as existential conditions) from composite forces (which encompass contact forces). Finally, we hint at how this model could answer some classical philosophical difficulties concerning forces and dispositions.

Upper ontologies are sophisticated systems that require an expressive language to be properly formalized and correctly implemented. This paper provides a formal study of one of these ontologies, called YAMATO, by providing an axiomatization in first-order logic of part of the main system. YAMATO, which has been available in OWL for some years and is used in research projects as well as in applications, is quite rich in terms of categories and relations. The system is also interesting from its ontological perspective as it presents a different combination of ontological choices with respects to todays popular upper ontologies. Here we isolate a fairly compact fragment of this system that covers important categories, such as Process and Role, and relations, such as Enacting and CausallyContributing. The axiomatization is a first step towards the full exploitation of YAMATO in information and computational systems.

We have built an instructional design support system called “FIMA-Light” which reasons about a teacher’s intentions from his/her lesson plan and automatically produces I_L event decomposition trees. The decomposition tree expresses the ways of achieving a learner’s state change that should be realized in a whole lesson in the form of a tree structure. In this paper, we discuss the difficulty of attaining the goals of university education without using our approach. We also report on practical use of FIMA-Light in teacher training at university in order to investigate changes in students’ awareness of teaching strategies brought about by providing them with I_L event decomposition trees.

In this paper, we discuss reuse of teaching strategies that schoolteachers employing in practice. One of the significant capabilities of teachers is to blend content knowledge and general pedagogical knowledge within a context. The authors carried on a case study of modeling practical teaching strategy of schoolteachers in order to facilitate reusing them based on an ontological engineering approach. As the result, the teacher could design lesson plans serving his different two intentions.

We have built an instructional design support system called “FIMA-Light” which reasons about teacher’s intentions from his/her lesson plan and automatically produces I_L event decomposition trees. In this paper, we discuss a particular use of I_L event decomposition trees produced by FIMA-Light in a teacher education program. First, we consider effective alignment between teacher education at university and teaching practice in the classroom. We also report on trial use of FIMA-Light in teacher education at university in order to investigate the usability of the information expressed by I_L event decomposition trees.

Both natural objects and artifacts have been studied from a variety of perspectives by the different sciences. One issue that has so far resisted philosophical and ontological investigations is the definition of a general notion of function capable of making sense of the functions attributed to natural objects, such as biological organisms, as well as of the functions attributed to artifacts, such as (designed) tools.

In this paper, we discuss the effectiveness of an ontological modeling approach in practice. Although a lesson plan is a document that describes the plan of a lesson, the design rationale behind it tends to be implicit. The authors have developed an ontology called OMNIBUS and a theory-aware authoring system called SMARTIES. This paper describes the result of the experimental use of them in the real task of schoolteachers.

In this paper, we wonder: How aware are learners of their metacognitive skills at studying? In order to respond such a question, we propose a student model to acquire, measure, and depict basic metacognitive skills of learners. Our metacognitive student model describes underlying concepts of knowledge and regulation domains. The first experiment reveals: Groups of college students own a wide gray-level scale of awareness of their metacognitive skills.

This paper discusses computer support for making a design of a lesson in a school teacher’s mind. Although school teachers usually describes the plan in a document called lesson plan, it is the result of thought and does not often have enough information about the design rationale behind it. The authors have developed an ontology called OMNIBUS and a theory-aware authoring system called SMARTIES. The purpose of this study is to examine the effectiveness of them through the practical efforts of deploying them to a community of social studies schoolteachers. This paper presents findings of the practical efforts and considerations of improvement of OMNIBUS and SMARTIES.

In this study, we have been developing a system called FIMA (Flexible Instructional Design Support Multi-Agent System) that dynamically supports teachers in designing instruction by facilitating their thinking ways according to the characteristics of those of expert teachers. In the present study, we focused on a support to facilitate teachers’ deep reflection and awareness of room for improvement of their lesson plans based on instructional/learning theories and best practices. In order to provide such support, we make use of the OMNIBUS ontology, which describes knowledge extracted from instructional/learning theories and best practices. In this paper, we describe this support function in detail and report results of an experiment carried out for evaluation of its effectiveness.

The purpose of this paper is to characterize some definitions of function in engineering and philosophy from an engineering point of view. To do this, this paper firstly discusses some fundamental kinds of function based on ontological distinctions. Next, based on them, we characterize our definition with justifications from the engineering view and present an ontological model of artifact function along the product life-cycle. Then, we try to characterize a philosophical definition of biological organs using the model. Next, we discuss function of a non-biological (non-organic) natural thing. Lastly, we characterize functions of an artifact, a biological organ and a non-biological natural thing based on another ontological model along the evolution of creatures.

This paper discusses computer-based support for self-reflection of teachers in a lesson design task. One of the keys to success in the design task is an alternating cycle of externalization of ideas and reflection resulting from those externalized ideas. However, it is difficult for teachers to externalize their ideas to generate effective reflection. This study aims at enhancing reflection by ontological modeling of the design rationale of a lesson plan. The result of a trial in which a teacher externalized the design rationale of her plan and investigated reflection generated in the trial is reported here.

In this study, we have developed a system called FIMA (Flexible Instructional Design Support Multi-Agent System) which supports teachers dynamically in designing instruction by facilitating their thinking in ways characteristic of expert teachers’ thought processes: 1) multiple viewpoints thinking, 2) contextualized thinking and 3) the problem framing and reframing strategy. We especially focus on instructional design that integrates the use of information and communication technology (ICT). In this paper, we show examples of concrete supports which the FIMA prototype system we have built provides.

While the importance of metacognition is widely acknowledged in education, some researchers indicate that the domain of metacognition is one that lacks coherence. In order to overcome this issue, it is necessary that each researcher explains what he addresses as metacognition by using his own or other people’s framework of metacognition. We propose a new framework for metacognition which explains what types of metacognitive activity occurs and what types of metacognition-driven learning they cause. With this framework, it becomes possible not only to identify what types of metacognitive activity or what types of metacognition-driven learning a computer system supports but also to propose new functions that support the various types of metacognitive activity and metacognition-driven learning.

This study, through the ontological engineering approach, aims at building a conceptual basis that encourages instructional designers in better understanding of learning/instructional theories, which mean that instructional designers can select and integrate appropriate strategies from theories within an instructional context. This paper proposes a methodology of structuring the theories in terms of strategies included in them, in which strategies can be structured independent of paradigms and theories.

Design of collaborative learning (CL) scenarios is a complex task, but necessary if the goal of the collaboration is learning. Creating well-thought-out CL scenarios requires experience and knowledge about different learning/instructional theories and practices related to collaboration. Inexperienced designers, who may not have all the needed knowledge to formulate pedagogically sound collaborative learning plans, may have difficulties to design CL activities. Thus, although CL has shown to be effective, it is not often used in classroom adequately. To tackle this problem, this paper presents an ontology for CL, that aims at modeling not only the learning activities, but also the rationale for their configuration in pedagogical terms. This ontology allows modeling the expected interactions among students as well as the mechanisms that promote or enhance collaboration structured across several sessions and involve individual and collaborative activities. Finally, the paper discusses an application of the presented ontology to support the design of pedagogically sound CL scenarios.

In sustainability science (SS) it is not only difficult to identify what needs to be solved but how to solve the problems once identified. There has been no consensus on underlying question of ldquowhat is structuring in SS?rdquo This paper focuses on articulating in the form of a reference model a set of required elements, functions, and actions for structuring SS knowledge and on realizing a part of that reference model by developing a prototype knowledge system for mapping relevant concepts and their linkages in SS. First, we develop a reference model composed of five layers. Second, we develop an ontology-based mapping tool as a tentative solution at layer 2 of the reference model. Third, we assess whether the developed tool is compliant with the reference model for SS. This study concluded that the developed tool can facilitate divergent exploration, the function of Layer 2.

Growth in the mobile services industry has remarkably increased in the number of mobile services provided, and present methods of service provision have proven insufficient to guide users efficiently to the services they need. To solve this problem, a task-oriented menu, which enables users to search for services by "what they want to do" instead of by "name of category", has been proposed. Construction of such a task-oriented menu is based on a task ontology modeling method which supports the description of user activity such as task execution and the solving of obstacles encountered during the task. This paper discusses a task ontology-based modeling method which supports the description of users' activity and related knowledge such as how to solve problems that occurs on the users and prevention method for accidents. Models described by our method contribute to checking, designing and improving mobile Internet services.

In this paper we present a B2B integration project, which aims to augment the added value of services instead of improving efficiency by automating processes. This paper introduces the VAlue Layered docUment Exchange (VALUE) model, which is a novel collaboration model adopted for this project. The key feature of the VALUE model is that partners exchange XML documents that are updated by adding elements for process information, such as the acceptance or rejection of a proposal, to received documents. Exploiting the extensible characteristics of XML, this model enables real business collaboration without complex process flow control. The project has demonstrated the advantages of a collaborative protocol based on this model in the Japanese retail industry. This protocol adopted ebXML MS (Messaging Service) for messaging over the Internet, and was the first case that applied ebXML to real business collaboration in Japan.

We can observe various kinds of interaction among members of a learning group during a collaborative learning session. It is difficult for even human users to analyze them in order to clarify what types of collaboration have occurred in the session and what educational benefits have been expected for the members through the session. So, we propose an interaction analysis support system that helps users to abstract the essence of interaction from raw protocol data, and to understand what types of collaboration have occurred in the session, and then infers educational benefits expected to be gained by the members through the interaction process.

In AI in education research community and related academic communities such as learning science (LS), instructional science (IS) and instructional design science (ID), a lot of research results have already accumulated and many sophisticated learning support systems have been built to date. The problem, however, is that it is not easy to build a good learning support system well-justified by such basic theories because they are not easily accessible for system designers/developers nor ready for engineering use. Imagine a theory-aware authoring environment, which can help designers/developers find, understand and utilize necessary LS/IS/ID theories to build a theory-justified learning support system. It must give a great impact on our community. The authors have some experience in building ontologies for learning support systems and LS/IS/ID knowledge as well as a road map towards a theory-aware authoring system. On the basis of development of a general framework of an ITS, we first designed a comprehensive ontology for ITS.

Intellectual synergy is a major source of high competitive power for an organization. Through the authors research project, we have been developing an environment, Kfarm, to support creating/inheriting organizational intellect. Characteristic features of Kfarm include a dual loop model which represents ideal processes of knowledge-level communication among personnel to create/inherit organizational knowledge. In this paper, they focus on collaborative learning support functions of Kfarm. This research seeks to clarify the essential role of collaborative learning in an organization and provide an appropriate opportunity for collaborative learning for organization members. Attaining the goal requires construction of a design model of collaborative learning and realization of design support functions into Kfarm. This paper first introduces learning aspects of organizational activities, Then, it roughly outlines Kfarm while focusing on collaborative learning support functions.

It is necessary that the relations between individuals and organizations be properly understood and support learning for knowledge inheritance, and encourage the creation, the spreading and inheriting of new knowledge. This paper presents an framework of information systems for knowledge management focused on a learning system in organization. Major characteristics of this framework are derived from “Dual loop model” which represents the flow of knowledge in an organization. Since these two things enable the framework to grasp the meaning of knowledge and the progress of organizational learning, it can provides appropriate support for knowledge management Then we will introduce two systems as concrete examples, namely a knowledge management support environment: Kfarm.

This paper describes topic identification for Japanese TV news speech based on the keyword spotting technique. Three thousands of nouns are selected as keywords which contribute to topic identification, based on criterion of mutual information and a length of the word. This set of the keywords identified the correct topic for 76.3% of articles from newspaper text data. Further, we performed keyword spotting for TV news speech and identified the topics of the spoken message by calculating possibilities of the topics in terms of an acoustic score of the spotted word and a topic probability of the word. In order to neutralize effect of false alarms, bias of the topics in the keyword set is removed. Topic identification rate is 66.5% assuming that identification is correct if the correct topic is included in the top three topics. The removal of the bias improved the identification rate by 6.1%. 1. INTRODUCTION Enormous speech data, such as TV news, can be stored in the data base as compu...

The paper describes automatic generation of speech synthesis rules which predict the accent component value (stress level) for the bunsetsu in long noun phrases. The rules are inductively inferred from a lot of speech data by using two kinds of tree-based methods, the conventional tree generation and the SBR-tree algorithm. The rule sets automatically generated by the two methods have the almost same performance and decrease the prediction error to about 14 Hz from 23 Hz of the accent component value. The rate of the correct reproduction of the change, that is increase or decrease, for adjacent bunsetsu pairs is also used as a measure of evaluation and the generated rule sets correctly reproduce about 80% of the change. Effectiveness of the rule sets is verified through a listening test. SBR-tree methods generate very compact rules which are easy for human experts to interpret and match with the former studies.>

A concept-to-speech (CTS) conversion system, SOCS (speech output from case structure representation), is described. For CTS systems, how to represent the input to the system is a very important issue. In SOCS, a representation based on case structure and phrase patterns, which is called concept representation, is converted into synthetic speech. SOCS plays a crucial role in a speech output interface which is designed as a general frontend of various intelligent performance systems (IPSs). The message transmission of the concept representation satisfies the requirements both from IPS and the speech synthesis component. SOCS has two new built-in mechanisms for direct control of prosodic parameters by a concept representation. The first is the pause marker which is generated along with words in the sentence generation. The pause marker is used both to insert pauses and to set the boundaries of the prosodic phrase component of F/sub 0/. The second is the prosody modification function (PMF) embedded in the custom templates. PMF controls the prosodic parameters for the prepared sentence pattern. The dialog management in a speech output interface based on SOCS is also discussed.>

The main objective of our research is to construct a continuous speech recognition system by using knowledge engineering techniques. The system simulates the behavior of a human expert who can recognize continuous speech by inspecting the trajectories of feature parameters such as formant frequencies. The expertise is embedded in the form of production rules. In the current implementation, we have 114 rules which are being updated. The introduction of production system to knowledge representation enables to cope with large amount of heuristics of speech recognition. Recognition rate of 85% was obtained for continuous speech of 30 second long uttered by three male adults. An environment for rule-base construction is also being developed.

The formulation of linear prediction analysis using the generalized inverse matrix is reviewed and Givens' reduction employing Gentleman's algorithm is introduced as a fast computational method to obtain the least-squares estimate for the prediction coeficients. An improved version of the sample selective linear prediction (SSLP) is described and some performance examples on nonstationary synthetic speech are shown in comparison with those by the ordinary linear prediction analysis and the proto-type SSLP. Finally, the short-term SSLP is proposed and its discrimination performance on voiced plosives is compared with those by the ordinary short-term linear prediction analysis.

Linear prediction method is one of the most frequently used analysis methods of speech. Covariance method and auto-correlation method of linear prediction often fail to make a precise analysis of speech because of the excitation source or fundamental frequency. In order to decrease the affect of the excitation source, various kinds of difference operations are usually employed for preprocessing. However, such preprocessings do not always work satisfactorily. Here proposed is a new approach to LPC analysis based on selective use of speech data to reject the data disturbed by the excitation source, and is called selective linear prediction method. The method is constructed aiming to improve the accuracy of analysis. First, the formulation of linear prediction is presented using generalized inverse matrices. Then, a successive computation is described based on Givens' reduction. The selective computation, which plays an essential role in our method, owes its efficiency to Givens' reduction. Finally the advantage of the proposed method is demonstrated by computer simulation using both synthetic and natural speech.

The present paper discusses a nonparametric algorithm for detecting clusters. In the algorithm a positive value called potential is associated with each datum based on dissimilarities. By defining subordination relations among data, hierarchical structure is introduced into the data set. As a result of the introduction of hierarchical structure, the data set is divided into some subsets called subclusters. A procedure for constructing clusters from the subclusters is also considered. The proposed algorithm can be applied to a very wide range of data set and has great ability to detect clusters, which is verified by computer simulation.

The present paper discusses a nonsupervised multicategory problem in terms of nonparametric learning. An algorithm for seeking modes of an unknown multidimensional probability density function (pdf) is considered by employing a hypercubic window function. The convergence proof of the algorithm is also presented. The discriminant function for multicategory problems is constructed by using the estimates of the modes of the multimodal pdf. An application of the mode estimation algorithm to nonparametric signal detection is described. The analytical result shows that our machine nearly converges to the optimal machine without supervision.

In this correspondence, an approach to unsupervised pattern classifiers is discussed. The classifiers discussed here have the ability of obtaining the consistent estimates of unknown statistics of input patterns without knowing the a priori probability of each category's occurrence where the input patterns are of a mixture distribution. An analysis is made about their asymptotic behavior in order to show that the classifiers converge to the Bayes' minmum error classifier. Also, some results of a computer simulation on learning processes are shown.