Multi-vendor based Internet of things (IoT) has become a popular concept, and autonomous systems have been considered effective to address complicated IoT control systems and service systems. However, applying autonomous systems to IoT has caused problems in managing consistent identifiers. To solve these problems in system management, we propose a structured identifier (ID), which can define the complicated structure of control systems and computer systems by using IDs on a tree structure, and relational links, which can describe meaning for subsets and networking by using structured IDs. Furthermore, we propose quantitative and qualitative management methods for autonomous systems by controlling self-information of structured IDs for retrieving information by using regular expressions. Finally, we evaluate whether the proposed methods can be implemented in real solutions and find that they enable more than 1000 elements to be managed in a machine management solution. Additionally, they solve problems in 700,000 kinds of business programs management in a mega-bank resilience support service use case.

Understanding unfamiliar source code is inherently difficult for a software engineer, despite its importance. Thus, an experienced engineer prefers to guess the intended behavior, rather than to trace it line-by-line, by combining semantic chunks found in the source code. It is, however, still hard for a system to help in this activity, for lack of ways of both representing semantic chunks and of preparing a rich dictionary of chunks. In this paper, an integrated framework for annotating and searching source code is presented. Since the research is still in its early stage, this paper focuses on the framework itself, together with a brief description of our prototype implementation. In the framework, each engineer gathers (annotates) semantic chunks that have the same meaning and interactively generalizes them to get a search pattern. As a result, a dictionary of semantic chunks together with their search patterns is incrementally created through engineer collaboration. To realize this, two representations are used: a tuple of nodes of an abstract syntax tree (AST) for a semantic chunk and a classifier on generative attribute vectors for search patterns.

Human daily activities are stored in various kinds of data representations using ICT devices nowadays, named lifelogs. It is highly requested to retrieve useful information from lifelogs because these raw data are hard to handle. Extracting human activities from these logs is promising to enrich our life. Context-awareness services can be provided depending on user activities extracted from these logs. Recently, a lot of people post a message called tweet within Twitter to show what they are doing, thinking, feeling, and so on. Tweets have potential to record human activities, because many people post tweets so frequently every day. This paper focused on the tweets to retrieve human behavior from them. The length of tweets are limited within short sentence, so this causes some difficulties. The users will use domain-specific terms and will post grammatically incorrect sentences to fit with the constraints. These make us hard to analyze tweets with grammatical manner or with dictionaries. To tackle them, we are applying character n-gram tokenization and naive Bayes classifier to extract appropriate behavioral information from tweets. Using n-gram tokenizer, domain-specific words can be identified and incorrect grammar can be handled. Our approach is examined using real tweets in Japanese. The index of precision, recall and F-measure shows the promising results. Some experiments have been carried out to show the feasibility of our approach. At this point, our system applied to Japanese tweets but it is applicable to any other languages.

We have been studying the use of "Rich Media" to support creative and intelligent human activities. Specifically, for over ten years we have been focusing on the 3D space as a "Rich Medium" and developed many 3D sketch systems that support the design of 3D objects. However, we found that designers in the real world do not use them. The fundamental problem is the lack of an indispensable function for using the 3D space. To overcome this problem, we have proposed "life-sized and operable" design principles. Although the new design concept made the 3D space truly useful and promoted the designer to use such a system, it revealed new problems, i.e., Limited design space. In this paper, we extend this "life-sized and operable" 3D sketch system by using three design spaces, which enables the user to traverse between 2D drawing and 3D drawing spaces, between miniature and actual sizes, between rough sketching and precise design, and among still, operable, and hap tic sketching.

This paper reports our experience with software development based on the Software Product Line (SPL) approach employed for Clinical Instrument Integration Management Software (CIIMS). CIIMS is the system software which systemizes heterogeneous clinical instruments. These instruments require their particular management so that various parts of CIIMS are forced to be changed. This makes it difficult to create development plans to connect new instruments to CIIMS. In this paper we summarize a new estimate method called the Architecture Domain Matrix (ADM) method which effectively solved this problem in our experience. In ADM each architectural element is further decomposed into clinical operation flow elements and core assets of software are extracted from these elements. This method estimates the CIIMS commonality with precision and finally enables to successfully connect new instruments. In addition this method provides a Work Breakdown Structure (WBS) and supports development team building. WBS is generated by collecting all the changes for each operational flow element. A development team suitable for change is organized by taking into consideration all the changes for each architecture element. We integrated three different instruments into CIIMS in 18 months after applying this method to a real project and achieved 2.5 times greater productivity with the embedded software than that with our previous non-SPL process.

We have been studying the creativity-centered media to ensure that systems truly support creative and intelligent human activities. However, it has gradually become obvious that current advanced support systems have a serious drawback: instead of promoting creative work, they often discourage creativity or let us stop thinking. In this paper, we focus on the 3D sketch system that supports the design of 3D objects by drawing them in the 3D space directly, because they are not used by designers in real fields but are just treated as a mere attraction in an amusement park. We propose three design principles, “Memory Capacity”, “Cognitive Mode”, and “Life-size and Operability”, which make the 3D sketch system truly useful for the designer. They have been gradually derived in the accordance with our cognitive experiment and developing series of 3D sketch system.

We propose a generalized inference method for constructing natural language communication. The method is used to obtain fuzzy quantifier Q' when “QA are F is τ ⇒ Q'(m'A) are mF is m'' τ " inferred (Q, Q': fuzzy quantifiers, A: fuzzy subject, m, m', m": modifiers, F: fuzzy predicate, τ: truth qualifier). We show that Q' is resolved step by step for a non-increasing type (few,...) and a non-decreasing type (most,...).

In this paper, we propose a method that affects inference results leading to a new interpretation of a truth qualification by adding a weight attribute to truth qualified fuzzy sets. With this method, we can obtain different inference results depending on the truth qualifiers by transforming a statement with fuzzy quantified and truth qualified natural language propositions. We applied our method to two examples transforming a fuzzy predicate of the natural language propositions and showed an effectiveness of the method.

In this paper, we report how we obtained inference results for fuzzy-quantified and truth-qualified natural language propositions - especially for those qualified by false. We obtained inference results, Q’s, for the inferences QA are F is false↔Q’A are mF is false, QA are F is false→Q’(mA) are F is false, and QA are F is false→Q’(m’A) are mF is m”false (Q, Q’: fuzzy quantifiers, A: fuzzy subject, F: fuzzy predicate, m, m’, m”: modifiers).

Unlike documents, annotation for multimedia information needs to be input as text, not in the form of symbols such as underlines and circles. This is problematic with keyboard input for non-alphabetical languages, especially the East Asian languages such as Chinese and Japanese, because it is labor intensive and imposes a high cognitive load. This study provides a quantitative analysis of the effectiveness of making annotations by hand during a note-taking task in Japanese. Although the lessons learned from this study come from Japanese text input, they are also generally applicable to other East Asian Languages which use ideographic characters such as Chinese. In our study, we focused on both the ergonomic and cognitive aspects and found that during annotation and note-taking task input by hand is more effective than input by keyboard. Finally, we anatomized the keyboard input problem and discuss it in this paper.

We propose an IF...THEN... rule-based inference method, which is necessary to construct a natural language dialog system and an expert system. The method is used to estimate a truth qualifier, tauB', when the input proposition is "QA are F is tau" and the IF ... THEN ... rule "IF Q'A' are F' is tauA, THEN Q"A" are F" is tauB" is given and the inference result is "Q"A" is F" is tauB' " (Q, Q', Q": Fuzzy quantifiers, A, A', A": Fuzzy subjects, F, F', F": Fuzzy predicates, tau, tauA, tauB, tauB': Truth qualifiers). We propose a method, which infers a result proposition for monotone Q's and show concrete application examples of using the method. Furthermore, we compare the inference results under various implication functions used for obtaining a truth-value fuzzy set of the rule.

The informal information can be so intuitive, emotional, personal, honest and subjective that it is very difficult to get them from the formal media. In this paper, we demonstrate a multimedia informal communication support system whose basic architecture is a combination of a wearable computer, a see-through head mounted display, a bone conduction speaker, and a 3D-pen. The user can create a "multimedia" graffiti such as a handwritten memo or a voice memo and place it in a real-world "multimedia" context such as at a certain location (by GPS), environmental sound, the real object (by RFID) and so on. The multimedia informal information is thus shared with others on the peer-to-peer self-organized network. We demonstrated the prototype system and conducted a preliminary evaluation

We developed a programming environment that promotes logic development in children. Dealing with the real materials in their play environments is important for children using this programming environment. Based on our analysis, we propose a concept model and the user interface for a play environment for children. We confirmed the effectiveness of the programming environment experimentally.

This paper presents a novel system which learns how the users want to control the entertainment robot with intuitive gestures. Two major problems are focused on this paper. One is how to distinct the user intuitive gestures, another is how to make the correspondence between the gestures and the control commands. Users want to use their own gestures which are not known a priori. These gestures must be classified by the systems by themselves. After the classification, the system must interpret the user intention to the control command which the user want to input. For instance, one may use waving hand gesture as the shutdown command, and another may assign the same gesture to the different command such as turning around. The primitive systems are implemented on the entertainment robot named AIBO. AIBO recognizes the gestures which are classified using Self-creating and organizing neural network. AIBO also learns how to interpret them into its command using Q-Learning technique. Some experimental results show the feasibility of the proposed approach.

Many household electrical appliances that use information technology have recently been developed. We can operate these appliances from anywhere, and research has shown that such appliances support users in their daily lives. The basis for supporting the user is detecting repetitive operation by the user. We think it is important for a home agent to detect user operation and consider the users feeling when they are operating the appliance. The home agent takes into account the degree of importance and pleasure of the operation pattern. In this paper, we propose a home agent that predicts the user's operation, detects forgotten operation and supposes a degree of importance and pleasure for an operation pattern and evaluated its performance in a simulated environment.

In this paper, we propose a generalized inference method needed for constructing a natural language communication system. The method is used to obtain fuzzy quantifier Q' when "Q are F is taurArr Q'(m'A) are mF is m" is tau" is inferred (Q, Q': fuzzy quantifiers, A: fuzzy subject, m, m', m": modifiers, F: fuzzy predicate, tau : truth qualifier). We show that Q' is resolved step by step for two types of Q, including a non-increasing type (few,...) and a non-decreasing type (most,...)

Recently, the information technology enables us freely to utilize various multimedia information. In fact, it is quite common to use three-dimensional image and the realistic 3D-sound. Most of leading information systems aim at making the best use of such three-dimensional media. But, the three-dimensional media is not always more powerful than the other media. In this paper, it is addressed that each dimensional media has its own strength and the suitable dimension of the media must be used for effective information output. To exemplify it, two systems with the seamless cooperation of multi-dimensional image and sound have been developed and evaluated. Finally the findings are applied to the design environment for the car exterior designer.

The importance and efficiency of backward reasoning in nonfuzzy reasoning has been stressed for a long time, especially in the case of expert systems and decision-support systems. The extension of this reasoning method to fuzzy theory, however, has never been considered. In this paper, the authors propose a definition of fuzzy backward reasoning based on the generalized modus ponens and show the necessity of considering interval-valued fuzzy backward reasoning. Then, the authors propose solving methods for fuzzy backward reasoning in the case of a rule with one or several conditions as well as in the case of several rules.

We are developing a natural language communication system called FLINS, which is short for Fuzzy Lingual System. The final goal of the project is to implement a lingual computer that can communicate and learn, both by being taught and on it own, through use of a fuzzy natural language. New design concepts, text-based architecture and fuzzy-centered architecture, to overcome the problems and limitations of the conventional systems are proposed. Next the problem solving by the three-layered fuzzy inference, and the meta-inference by the combination of the three-layered fuzzy inference and the self-wondering mechanism are described as the natural language processing engine of FLINS.>

In this paper, we propose a new rule-based method to determine exactly all the widest solution sets of a max-min fuzzy relational equation. As they can be applied to many fields of fuzzy logic, fuzzy relational equations are of great importance; therefore, many researches have been carried out on the subject and many methods have already been proposed to solve the various kinds of fuzzy equations that can be defined, especially the so-called max-min equations. One of the main consequences of the use of the max and min operators is the non uniqueness of the solution. Indeed, when a max-min fuzzy equation has solutions, there are several solutions which can be grouped in intervals. However, most of the existing methods do not enable to calculate the widest solution sets only, often leading to calculate non-maximal solution sets, that is, solution sets included in wider sets. This often results in unnecessary calculations, requiring huge amounts of memory and time. The method we propose here enables to determine rapidly all the widest solution sets of a max-min equation, and those sets only. The use of symbol-valued matrices enables to define simple rules and makes the method very simple to apply.

The inverse problem of the aggregation of fuzzy sets is addressed: the result of the aggregation of several fuzzy sets being known, the aim is to determine the initial sets. The case of the aggregation of two premises is studied first and a rule-based method is proposed to determine exactly all the widest solution sets of the problem. A recurrent algorithm is then proposed to solve the problem in the case of any number of fuzzy sets. The relevance of the proposed criteria enables to cope with the exponential complexity of the problem, and to define the widest solution sets only. Examples are provided to illustrate how the solving algorithms can practically be applied.