Yasuhiro Hayashi

This paper proposes a spatio-temporal and categorical correlation computing method for induction and deduction analysis. This method is a data analytics method to reveal spatial, temporal, and categorical relationships between two heterogeneous sets in past events by correlation calculation, thereby finding insights to build new connections between the sets in the future. The most significant feature of this method is that it allows inductive and deductive data analysis by applying context vectors to compute the relationship between the sets whose elements are time, space, and category. Inductive analysis corresponds to data mining, which composes a context vector as a hypothesis to extract meaningful relationships from trends and patterns of past events. Deductive analysis searches past events similar to a context vector’s temporal, spatial, and categorical conditions. Spatio-temporal information about the events and information such as frequency, scale, and category are used as parameters for correlation computing. In this method, a multi-dimensional vector space that consists of time, space, and category dimensions is dynamically created, and the data of each set expressed as vectors is mapped onto the space. The similarity degree of the computing shows the strength of relationships between the two sets. This context vector is also mapped onto the space and is calculated distances between the context vector and other vectors of the sets. This paper shows the details of this method and implementation method and assumed applications in commerce activities.

Dynamic routing with combinations of mobility and activity is expected as new methodology for supporting sensitivity to various contexts for traveling. It is important to realize the dynamics by integrating “mobility and activity” in physical and cyber spaces. This paper presents a mobility and activity integration system for making routing plans from an original point to a destination with a scenario as “sensitivity to context” on the route. The “sensitivity to context” expresses reactions to the intentions and situations of a moving user. This system applies semantic computing to find out the appropriate mobility and activity, that dynamically calculates semantic associations between user’s intentions and mobility services. This system makes a moving plan reflecting “sensitivity to context” created by query creation operators for synthesizing and expressing “everyday intention” and “mobility situation.” This system has a distance calculation function for “feature value vectors” expressing the means of mobility and the features of facility spots, and outputs some expected means of moving towards the destination with activities on the route.

© 2018 IEEE. In this paper, we present a real estate search and evaluation system corresponding to regional diversity. This system can be regarded as a real estate search system using location information as three factors respectively: (1) physical environment, (2) social environment and (3) traffic and communication. With this system, a prospective buyer of real estate are able to search for a place where the living environment is good and the real estate price is low, where the 'potential' as real estate is high. Generally, a prospective buyer selects a real estate by his/her qualitative judgement, intuition or even a biased view on the place. The features of the system is in calculating the semantic distance between the needs of prospective buyer and each real estate's condition, which enables the buyer to consider the regional diversity quantitatively. The main objective of our research is to create a system to contribute to the effective utilization of vacant houses and lands in an aged society with dwindling birthrate and a declining population, and support people's pursuance of Quality of Life (QOL).

In this paper, we present information providing a method to realize semantic representation of train service situations by a combination of sign-logo images. Through this method, multiple images having visual meanings such as pictograms, icons and sign-logos are combined to represent images to express train service situations in the railway space based on the knowledge of the railway company such as transfer ways in accidents. Features of this method are as follows: (1) To express events occurred in railway space by combining multiple images as visual communication based on '5W1H' that corresponds with human communication and information understanding. (2) To dynamically calculate the correlation between an event and meaning of the combined sign-logo images. (3) To be associated with the event of a railway space including an attractive tour guide to foreign visitors by combining sign-logo images. We have developed an experimental system as a digital signage and have applied the method in order to realize a sign-based guide at all train stations for foreign visitors in Japan. The effectiveness and feasibility of this method are shown in this paper.

We have put into practice the flipped classroom as a way of utilizing e-learning contents in our computer-programming course since 2013. The main feature of this practice is to use most of the time usually dedicated to lecture for practicing by assigning the students the e-learning materials as preparation before the class. We gave the students homework to learn vocabularies and grammar of the C programming language. This decreased the time a teacher spent lecturing and the students were assigned applied-problems to make practical software in addition to conventional basic problems in training. Our goal is to maintain the students' motivation to learn the computer programming through the sense of accomplishment that each student obtains by finishing practical assignments in the training. We confirmed the effectiveness of this approach by comparing examination scores between last year and this year, and putting questionnaires to the students. Additionally, we analyzed the learning situation of the students who were week in programming. The results are shown in this paper.

This paper presents a combined-image query creation method for expressing user's intentions by combining multiple digital images for image retrieval. This method uses image databases provided for query-creation and performs several set-operators to express user's imagination by combining user's imaginary images and real scenes. The user's intentions are expressed by the operation of subspace projection in the image feature space. This method makes it possible to create an imaginary image as the combined-image query for expressing user's intentions by combining several images and operators in the query creation process. The important feature of this method is to use shape and color features for expressing imaginations by extending our previously proposed method. This paper shows several experimental results to clarify the feasibility and effectiveness of our method.

Image-query creation for expressing user's intentions is essential for efficient utilization of massive digital image resources. This paper presents an image-query creation method for expressing user's query intentions by combining multiple images for Content-based Image Retrieval. The image-query for expressing intentions is created by combining image resources in image aspects such as colors and objects. This method realizes image-query creation by the drawing on user's imagination to express intentions such as the addition of the color, the removal of the object, the conversion and the scaling. This method uses multiple actual images and applies several query-creation operators calculating image features for expressing intentions to those images. This paper shows implementation of the experimental system where image queries are expressed with specific intentions to clarify the feasibility and effectiveness of the proposed method with experimental results.