Hyperthermia treatment is a kind of cancer thermal treatment based on that tumor are weak at a temperature of 42-43 degrees Celsius. A radio frequency (RF) interstitial hyperthermia treatment is operated with needle electrodes. In clinics, when a doctor performs surgery with this thermal treatment, it is needed to precisely recognize the needle insertion positon and angle inside the human body. Accordingly, medical doctors are operating with an X-ray CT. In this study, we developed a virtual insertion simulator with hand tracking sensors for planning and training effective heating before the operation. This virtual reality system measures the operator's hand position precisely, using two hand-tracking sensors arranged orthogonal to each other to cover blind spots. We experimented with ager phantom and compared the accuracy between one and two sensor systems. From the measurement results, it was found that when using two tracking sensors, the positioning accuracy improved in every direction. The differences between actual measurement data and that of the VR simulator were less than 2mm in every direction. By using the developed VR insertion simulator, medical doctors can plan and train more easily and precisely for effective RF interstitial hyperthermia surgery.

We propose essay development schemata to support learners in English essay writing. The schemata are expressed by unified vocabulary in unified level of detail. Since essay structures are expressed as such schemata, learners will be able to know what the structures of essay exist, recognize how each structure is different, and what kinds of information are necessary for composing a type of essay. Computers, moreover, can support learners in composing essays by referring to the schemata as the knowledge of the logical structures of English essay.

Learning by posing arithmetic word problems is well-recognized as an effective means to mastering the use of solution methods; however, several learners cannot pose problems using words. In problem-solving exercises, if a learner cannot understand what is expressed in a problem statement, an illustration of the scene expressed in the statement can help the learner understand. Therefore, in this paper, we propose learning by posing problems with illustrations instead of words. One of the purposes of learning mathematics is to acquire the ability to derive a numerical relation from a scene and to associate a calculation expression with various scenes. We expect that posing problems via illustration and without words is an effective way for beginners to learn. In the problem-posing exercises, learners construct various types of problems. Teachers have to evaluate each posed problem and advise learners on the basis of the evaluations. This task places a heavy burden on teachers. Therefore, we developed a computer-based environment for posing problems using illustrations. The environment provides a learner with a calculation expression and illustrations. The illustrations can be disassembled into several figures. A learner assembles an illustration that describes a story of arithmetic problem that correspond to the calculation expression by combining the figures. The learner uses no sentences in this problem-posing exercise. The environment diagnoses the illustration problem and produces advice to the learner. We conducted a preliminary evaluation of the environment to confirm that a learner who cannot pose problems via words was able to pose problems using illustrations. Our results were promising, indicating that our environment provides a means for learners who cannot pose problems via words.

In recent years, research attention on smart grid comprising distributed power generators has increased. To produce electricity in the smart grid, many micro grids (MGs) may exploit various renewable energy resources. Because the production capacity of renewable resources cannot be controlled, the MGs often require the power plants to provide power for them. However, the power loss between each MG and the power plant is larger than that among the MGs. To alleviate this power loss, we propose a game theoretic coalition formulation strategy for the MGs dubbed GT-CFS. Our proposed GT-CFS allows the MGs (belonging to the same macro station (MS)) to autonomously cooperate and self-organize into a partition composed of disjoint MG coalitions. Also, GT-CFS enables the MGs, in a distributed manner, to decide whether they will remain in the coalitions or not upon environmental changes, e.g., the variation of the power demand of the MGs. Within every coalition, MGs coordinate the power transfer among themselves as well as with the MS, in a fashion to optimize a utility function, which captures the total losses over the power distribution lines. MGs in the same coalition will distribute the extra profits (i.e., payoff) produced from forming coalitions by their “Shapley value.” Through computer simulations, we demonstrate that the proposed GT-CFS reduces the average power loss per MG significantly in contrast with the conventional noncooperative approach.

We proposed a design method to automatically generate an educational game by substituting the cards of an existing card game for new cards that have practice problems written on them. However, several games in which most players rarely solved problems were created by the method. Therefore, this study examines the reasons why they rarely solved problems. We conducted an experiment that asked test subjects to play useful and useless educational games and their reactions were videotaped. The video recordings and interviews suggest that few subjects solved problem in playing the educational games had no opportunities for solving problems to predict the future game state that would result from each choice to make a favorable choice. On the other hand, all subjects solved problems in playing the educational game had opportunities for the prediction. On the basis of the results, this study also organizes the rules that provides the prediction, and develops a system that detects useless educational games. The results of experimental evaluations of the system suggest that the detection system can detect useless educational game by the detection of the rules for the prediction.

Smart grid has emerged as a promising technology for enabling bi-directional communication between the power company and its users to facilitate intelligent, robust, and resilient next generation power grid systems. Through this technology, both the power company and its subscribers can be equally benefited, not only from economic point of view, but also in terms of environment-friendly quality of power usage. One important challenge for the smart grid designers is the demand side management, which can lead to avoiding the peak hours and reducing the cost for the consumers. In this paper, we address the power balancing challenge for the smart grid and discuss different solutions including game theoretic methods and demand control policies. Also, we present our novel demand control policy for achieving an effective management of the power consumption. Computer simulations demonstrate the effectiveness of the proposed policy compared to existing ones.

In this paper, we present a design of penalties against the action in contravention of the rule to discourage the tendency of unthinking and useless plays, observed while playing the automatically-generated educational games by our design method. Monitoring player’s activity and penalizing illegal moves are potential ways of preventing unconsidered activities. Because of the illegal moves and adequate penalties are strongly linked in each educational game, it is necessary to design the penalties individually for each educational game, therefore, we investigated the automatic design of penalties for educational games, generated by the EPIC method. We also introduce a function to automatically implement the penalties, and report the experimental evaluations of educational games with penalties.

Distributed power generation, using renewable energy, has been attracting attention to cope with global environment issues; a microgrid is a promising configuration for distributed power generation. To augment the stability and efficiency of the microgrid, an intelligent control, which considers the restrictions and characteristics of each unit, is indispensable. It can be achieved by constructing an efficient operation schedule for each power plant in the microgrid, depending on energy demand, and predicting passive power generation. The operation scheduling is regarded as a constrained optimization problem, which must have nonlinear characteristics in case of actual systems. Although several methods using metaheuristic optimization have been proposed, it would be trapped into a local minimum in some cases. In this paper, we statistically analyze operation schedules, computed for an actual power network of the demonstrative project. In addition, we conduct an investigation of the relationship between the input parameter space and the solution space, which can be exploited to obtain more appropriate initial solutions leading to better and faster converging solutions.

We previously implemented an authoring system to generate a learning environment based on a card game expressed in a flowchart . We improved the authoring system to automaticall y generate a learning environment by using words or sentences drawn from the rules of card games . The improvement is based on a card game model that is a structured representation of words and sentences from the rules of card games . In this paper, the card game model and the improved authoring system are introduced. The experimental evaluation of the improved system is also reported.

In this paper, we describe developing and evaluation of a learning environment for Solution-based Problem-Posing in the case of multi-digit subtraction. One of the ways to learn by problem-posing is to make learners pose problems which can be solved by a solution. We call the type of problem posing Solution-based Problem-osing. The Solution-based Problem-Posing helps the learners understand the solution. In the case of multi-digit subtraction, however, it is difficult to provide the solutions directly because the solutions in the multi-digit subtraction are complex for learners who are elementary school students when they learn them. We suggest a method they are required to solve problems to be conscious the solution of the problems and then pose problems based on the solution.

We have already proposed and implemented an automatic generation method of learning games. However, we also found that a few generated learning games were not useful for learning. Therefore, we propose detection method of the low efficient learning games and improvement method of the detected games in this paper. Automatic detection function has been implemented. We also report the results of experimental evaluation of the detection function and the improvement method of the detected games.

This paper presents a support system for organizing an English paragraph for users who have insufficient knowledge of English paragraph writing. The system infers the user's intention to compose a paragraph, organizes and proposes some outlines of a paragraph, and reports missing information which is necessary for completion of organizing the paragraphs. We have investigated the usefulness of the system by trying out it on subjects who have little knowledge of paragraph writing. Although several points need to be improved, the system was found on trial to be useful for such users.

In this paper, an error-awareness learning environment targeting the bugs of multi-digit subtraction is described. The authors first introduce the block-box model where the minuend is embodied as blocks and the subtrahend is embodied as boxes. In the block-box model, the process of subtraction is embodied as concrete manipulation of putting the blocks in the boxes. The bugs in multi-digit subtraction can be visualized as irregular manipulation of the blocks and boxes. They have developed a learning environment where a learner subtracts a multi-digit number described with blocks and boxes by direct-manipulation. The learner then can reconstruct an erroneous subtraction including a bug with irregular manipulation of the blocks and boxes. Through this reconstruction, they expect that a learner will increase his/her understanding about the procedure of subtraction. In this paper, an experimental evaluation of the learning environment is also described.

This paper describes a computational method of complexity of a question for an adaptive question and answer function in an intelligent support system for English learning, and its evaluation. To realize adaptive question and answer, systems should generate questions depending on both educational intentions and learner's understanding state. For generating suitable questions for a learner automatically, systems must know the factors which influence difficulty of questions, and have the ability to calculate difficulty. Difficulty is composed of a learner dependent part and an independent part. The former is evaluated by referring to a student model. The latter is defined by enumerating factors which influence complexity of questions. We present a definition of complexity of questions along learners' answering process. We also describe experimentation of comparing the complexity of questions calculated by computer with the complexity evaluated by human.

A learner who can solve a problem cannot always understand the problem adequately. In order to deeply understand a problem, it is effective that he/she poses problems which can be solved by the solution method of the problem. Moreover after solving and posing problems, it is important for him/her to consider and indicate relations between the problems solved or posed by him/her. In order to let the learner think about the relations, the authors propose a support environment for learning by describing "problem map". The "problem map" is a kind of semantic network where a node is a problem and a link describes relations between two problems. The authors are developing a support environment for describing a problem map in arithmetic learning. The environment cannot only provide learners with workspace to describe problem map, but also feedback based on diagnosis of the described problem map. Additionally, the problem map can be used as a structured problem source for adaptive Web-based problem practice which is generated based on the problem map.

Learning games are promising to realize highly motivated learning. We categorize the methods to design computer-based learning game in the following three: (1) combination method, (2) fusion method, and (3) simple simulation method. Fusion method is a method to design the learning game such that the learning skills of this game are regarded as a learning activity. We have developed a learning game with this method targeting learning by problem posing of arithmetical word problems. In this paper, we explain the fusion method as a design method of a computer-based learning game. Then, the learning game of problem posing of arithmetical word problems is introduced as a design example of the fusion method. Cases of the use of the game at elementary school are also reported.