Jun Hakura

Intelligent human interface based on mental cloning-based software

This paper reports on our experience in adapting emotional experiences of the software engineers in the evolutionary design of software systems. This paper represents the progress report on the development relative to the state of art needed to have multidisciplinary technologies for establishing the best harmonica engagement between human user and software application, based on cognitive analysis. The best performance related engagement has been achieved using together both the facial and voice analysis. And through it, we have measured (collectivized and quantified) and observed the user behavior, and accordingly enhanced the engagement by generative interactive scenario. The approach has been experimented using a famous literature person (Keni Miyazawa).

Virtual doctor system (VDS): medical decision reasoning based on physical and mental ontologies

Human computer Interaction based on emotional modelling and physical views, collectively; has been investigated and reported in this paper. Two types of ontology have been presented to formalize a patient state: mental ontology reflecting the patient mental behavior due to certain disorder and physical ontology reflecting the observed physical collected exhibited consequences of such disorder. These two types of ontology have been mapped and aligned using OWL-S and SWRL for reasoning purposes. We have constructed an integrated computerized model which reflects a human diagnostician as computer model and through it, an integrated interaction between that model and the real human user (patient) is utilized for 1st stage diagnosis purposes. The diagnostician knowledge has been utilized through UMLS for testing, and the integrated mapping of the two views been represented through OWLS framework. The reasoning instantiation is done using SWRL and RACER integrated on Protege 4.

Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies

The paper discusses reasoning application for decision making in medical diagnosis. This is to reason on medical concepts that are viewed on two type ontologies; namely physical and mental. We highlighted in this position paper issues on fuzzy reasoning by aggregating two types of ontologies that are used to formalize a patient state: mental ontology reflecting the patient mental behavior due to certain disorder and physical ontology reflecting the observed physical behavior exhibited through disorder. Similarity matching is used to find the similarity between fuzzy set reflected to mental fuzzy ontology, and physical fuzzy ontology. The alignment is projected on medical ontology to rank attributes for decision making. We apply aggregate function for ranking attributes related to physical object. In the same time, we apply harmonic power average aggregate function fuzzy for ranking attributes related to mental objects. The alignment of these two aggregate function produce weighted ranking order fuzzy set for medical decision making for diagnosis. The paper highlights these issues as new challenges extending intelligence reasoning of VDS.

Multiviews ontologies alignment for medical based reasoning ontology based reasoning for VDS

Two views representation for patient diagnosis is presented, to reason to examine medical status for patients. Emotional modeling and physical views, collectively; have been investigated and reported in this paper. These two types of ontology have been presented to formalize a patient state: mental ontology reflecting the patient mental behavior due to certain disorder and physical ontology reflecting the observed physical behavior exhibited through disorder. These two types of ontologies have been mapped and aligned for reasoning using a simple Bayesian Network for causal reasoning to define what we call as simple case diagnosis. We have constructed an integrated computerized model which reflects a human diagnostician as computer model and through it; an integrated interaction between that model and the real human user (patient) is utilized for 1st stage diagnosis purposes‥

Morpho-functional machine: design of an amoebae model based on the vibrating potential method

Abstract Soft-mechanics is a new research area in the field of developmental robotics. This paper reports on the methodology and results of our application of soft-mechanics to the problem of imitating amoebae-like motion through the fusion/coordination of hard- and software technology. This paper describes the development of a morpho-functional machine able to imitate amoebae motion, and the application of vibrating potential methodology to control this machine. Our efforts resulted in the development of a new field technique known as the vibrating potential field [H. Yokoi, Y. Kakazu, An approach to the traveling salesman problem by a bionic model, HEURISTICS, J. Knowledge Engrg. (1992) 13–27] and in a new parameter tuning method inspired from thermodynamics [H. Yokoi, T. Mizuno, M. Takita, J. Hakura, Y. Kakazu, Amoebae like self-organization model using vibrating potential field, Proceedings of the A-Life V, International Conference of Artificial Life V, 1996, pp. 32–39]. The field model produces self-organizing gathering behavior through the physical interaction of potential fields. The computer simulation shows that characteristics typical of swarm intelligence such as, gathering toward energy, thermotaxis, and obstacle avoidance, developed in the amoebae model. These characteristics were applied to the design and construction of three types of robotics-based physical system. The results of this research show the patterns of behavior which morpho-functional machines are capable of producing.

Explorations of perceptional mechanisms for adaptive agents

The environment in the real world has an almost infinite number of events. From a Cartesian point of view, these events consist of more detailed factors. Those factors often correspond to the physical properties of the environment and this renders symbolic AI powerless. However, affordance, i.e. the availability of behaviours with respect to the environment, uses functional properties of which it is possible to be directly aware. To make the agent more adaptive, the useful information is obtained by the agent itself. This paper describes two perception mechanisms that have possibilities to allow the agents to perceive the affordance through learning. The mechanism is aimed for the perception of the environment and the self-perception, respectively. The computer simulations and some preliminary experiment by the real agent, a vehicle with vision system, show the possibilities of the mechanisms.

Virtual Doctor System (VDS) and Ontology Based Reasoning for Medical Diagnosis

VDS is a system built as intelligent thinking support for assisting medical doctor in a hospital to do medical diagnosis based on the avatar of that doctor. The medical knowledge is also collected from the doctor based on his/her experience in diagnosis. The avatar construction is mimicking real doctor. The avatar interacts with patients through their voices, and other sensors to read patient mental state and physical state that are used in aligned manner to assess the patient sickness states through Bayesian network. The physical view is represented as physical ontology. The mental view is represented as mental ontology. These two ontologies aligned on medical knowledge for diagnosis and reasoning based on similarities computation. These two types of ontologies have been mapped and aligned for reasoning using a simple Bayesian Network for causal reasoning to find related query decision case based diagnosis collected from expert doctors. The system is implemented and tested. We have constructed an integrated computerized model which reflects a human diagnostician and through it; an integrated interaction between that model and the real human user (patient) is utilized for 1 st stage diagnosis purposes recalled as simple cases.

Multiviews ontologies based reasoning for medical diagnosis in VDS

This paper examined issues on reasoning in Virtual Doctor System based on two views representations for patient diagnosis. This is reason on similar medical concepts that are viewed on the presented ontology, to reason on medical status for patients. These two types of ontology have been presented to formalize a patient state: mental ontology reflecting the patient mental behavior due to certain disorder and physical ontology reflecting the observed physical behavior exhibited through disorder. These diagnosis issues are represented through concepts. Patient observations are reflected on these concepts for similarity calculation that produce decision making based query. These two types of ontologies have been mapped and aligned for reasoning using a simple Bayesian Network for causal reasoning to find related query decision case based diagnosis collected from expert doctors‥ We have constructed an integrated computerized model which reflects a human diagnostician as computer model and through it; an integrated interaction between that model and the real human user (patient) is utilized for 1st stage diagnosis purposes.

Affordance in Autonomous Robot

It is essential for the autonomous robots in the real world, filled with enormous amount of information, to catch only the useful and related information to their actions. Affordance would be one of the key-concept to be realized in the autonomous robots to make them able to perceive such useful information. This paper, therefore, tries to realize Affordance in an autonomous robot by introducing Inner Perceptual Model (IPM) as a field that will make the sensory inputs as a Grounded Symbol. An attempt to realize an emergent mechanism of Affordance is carried out by means of IPM, Active Sensing System, and Information Processing System. Four necessary-conditions to be satisfied are introduced to clarify whether the Perceptual Pattern in IPM could be the grounded inner representation of the environment. Computer simulations show the possibility that IPM would be an inner representation of the environment as Grounded Symbols. Moreover, the computer simulation shows possibility that proposed mechanism can distinguish the environment consists of the other robots from those consists of the obstacles. As a conclusion, we come to a hypothesis that the available action set recollected from observed sensory inputs corresponds to Affordance, and Affordance for robot.

Virtual Human Interaction based on Emotional Cognition

This paper is presenting progress status of our project named as emotion based reasoning for constructing a virtual emotional interactive human model. It is based on a person model, whose emotional characteristic been extracted from his work and other physiological, observations. A prototype of the system has been constructed for such experiment and based on famous Japanese writer namely Miyazawa Kenji.