Masanobu Numazawa

Education and learning support system using proposed note-taking application.

Recently, development and offering of digital textbooks, educational materials, and educational platforms have begun in the field of education. In addition, with the rapid penetration of networks and proliferation of powerful digital devices capable of editing, some note-taking applications such as Note Anytime and OneNote are released by each company. These applications can create attractive handwritten notes on tablets and smartphones through an intuitive interface. Furthermore, linked to the cloud storage service, they can allow multiple users to edit documents together and share information.

A hybrid Particle Swarm Optimization considering accuracy and diversity of solutions

Particle Swarm Optimization (PSO) is an optimization method that emulates the behavior of creatures such as a flock of birds or a school of fish. Two typical PSO information exchange formats are the Gbest model and the Lbest model. The Gbest model is the most basic model, but this model can converge quickly on a solution and may become trapped at a local solution. On the other hand, the Lbest model converges slowly on the solution but its global search capability is better. In this study, we propose a method of remedying the drawback of PSO in that it tends to become trapped at a local solution, by maintaining the diversity of the search by a global search using the Lbest model in the early stages of the search, then switching to a local search by the Gbest model in the final stages. We also confirm the validity of this method by simulation experiments using benchmark problems. As a result, we confirmed that accuracy of discovery of the optimal solution was increased, although convergence on the solution was somewhat delayed.

Logic for Multi-path Message Forwarding Networks for Mobile Agents

We discuss how mobile agents, moving in the Internet from node to node, can communicate with each other by forwarding messages in a robust way. As a solution, we present the general idea of a class of communication networks called the multi-path message forwarding networks (MMFNs), which can transmit the messages to mobile agents at the current location in a robust way based on multiple paths between the nodes and the target. The networks are formally defined in terms of graph theory, and the dynamic nature of the networks (i.e., how they evolve) is represented by a logical system, named \(\mathcal{L}_{n}\), consisting of six inference rules. It is shown that the system is sound in the sense that it generates only MMFNs. A computational interpretation of \(\mathcal{L}_{n}\) is also discussed.

The effect of education and learning using note-taking application

In recent years, in each stage of education from elementary to high school in Japan, the focus has been on teaching/learning programming. However, it cannot be said that all students are able to learn programming technology. Difficult problems exist in teaching programming because of differences in student achievement levels. These differences are found at the elementary and middle school levels of course, but are even more obvious at the high school level where courses begin to separate into humanities, science, and other fields.

A travel scheduling system based on spot evaluation

In recent years, with the rapid growth of the Internet, the user scheduling a travel can make own schedule not only using the package tour that a travel agency offers but also searching for the information about the travel spot that oneself wants to go. However, it is not easy for a user to search for the information about the destination and to collect it. It is more difficult to use obtained barrage of information and to make a schedule effectively. Therefore, without time and effort, it is very effective to make a schedule from the first image and interest for the destination. In this paper, we propose a system which makes a travel schedule by using the first image and interest for a destination as input data, without searching for the detailed information about the destination. In our proposed system, a schedule is made based on a time evaluation value and a spot evaluation value, which is calculated according to a subjective evaluation value and an objective evaluation value. On a selection screen displayed based on the schedule tree, the user can decide a schedule by selecting a spot which wants to go in sequence. As a prototype of our system, we implemented it for OKINAWA tour.

A Reflective Language Based on Conditional Term Rewriting

Meta-computation is a computational mechanism that allows computational systems to read and modify meta-objects that represent the current state of its own computation. Implementing meta-computation by high-level language enables us to access meta-level with high-abstract interface. In recent years this notion can be found in several fields of computer science and artificial intelligence. In particular, in the field of intelligent systems meta-computation is often called meta-inference and plays an important role for designing complex systems. We introduce reflective-computation mechanisms into a conditional term rewriting system-based language and discuss about their implementation and application.

Improvement of the modified low-first method for iterative learning

The learning assistance systems that use computers are a study format that is suitable for individualized study, they can determine and manage the learning situation such as each learners study history and results, and they provide a learning environment that is tailored to each persons learning pace and degree of comprehension. The Modified Low-First Method is an iterative learning method which is based on the psychological perception of the spacing effect and which decides on an effective and efficient sequence for presenting items in accordance with responses. In this research, we tried out some extensions which improve the presentation spacing between study sessions with respect to the Modified Low-First Method and also prevent unnecessary iterations, to present the study materials efficiently in long-term iterative learning, and have tested and verified their effects. We add three extensions to create an effective and efficient learning method for use during repeats of iterative learning by the Modified Low-First Method: “Extension 1: The initial item presentation sequence is in accordance with the item exclusion sequence of the previous study session”, “Extension 2: Items recalled at the first presentation are excluded at that point” and “Extension 3: Items that had been excluded before the study was interrupted are presented once immediately after the study is resumed”.

Meta-computation in conditional term rewriting systems

We propose a framework of conditional term rewriting systems equipped with meta-computation supported by basic mechanisms called meta-transformation and base-transformation. The arguments of a redex, the context around the redex and the current set of meta-conditional rewrite rules are considered as meta-level objects in our system, and by the meta-transformation they are transformed into base-level objects. The base-transformation transforms base-level objects called meta-representation into meta-level objects.