Human Interface and the Management of Information: Visual and Information Design

In this research, we consider HSP/HSC as users, not as a medical treatment for HSP/HSC, and introduce the process of considering what value can be provided to them and proposing products. In this study, design students used design thinking to create an experiential prototyping of a product proposal for HSP/ HSC. The process could be divided into five parts. By guiding the student’s interest and illustrating and carding the research, we were able to identify points for co-creation. In addition, the question of what is valuable for HSP/HSC was prototyped, focusing on physical perception and psychological states. This prototype uses the sense of warmth and a teddy bear-like shape, a metaphor for acceptance, to support a state of relaxation. The next step is to test the effectiveness of this prototype. Furthermore, in order to achieve co-creation, it is necessary to examine the development process using prototypes in order to involve all participants and stakeholders and have specific discussions. It is also necessary to develop skills and approaches for development process.

In recent years, with the advancement of technology and globalization, commoditization has been progressing in various markets in Japan. Therefore, in recent years, brand building has been attracting a lot of attention as a means of “de-commoditization” to break away from the current market. However, due to the lack of knowledge about branding among Japanese managers, few companies are working on it. In this study, we focused on the beauty esthetic industry in Japan and analyzed the effects of prior expectations and satisfaction on the brand value of companies.The results showed that there was no significant difference in the positive impact on brand value between high and low prior expectations. On the other hand, the negative impact of low prior expectations on brand value was more than twice as large as the negative impact of high prior expectations.Considering the negative impact on the brand, this study suggests the necessity of increasing the level of prior expectations, contrary to the argument that prior expectations should be controlled not to be too high to prevent the negative divergence between expectations and satisfaction. As for the negative divergence, it is necessary to control it using causal attribution and Cognitive Dissonance theory.Since the results of this research are very abstract, it is unlikely that individual managers will implement strategies based on these results. We will analyze what specific items are more effective in managing expectations and study them to the point where they can be incorporated into concrete strategies.

This paper proposes a model of human creative activities using the framework of wisdom science. The two main components of the model are the concept processing and image processing modules, which function in parallel with information exchange links between them. The model is also discussed related to the model of tacit and explicit knowledge. The concept of system science serves as the basic framework for the modeling and analysis.

The purpose of this study is to rebrand the Forest Notes product and service through a case study with an audio company. First, we conducted a research on the image of the audio company. Among college students around the age of 20 who were researched, the awareness of the audio company was low. This is thought to be because there are few touch points in media familiar to university students. On the other hand, research has shown that there is trust in technology. Next, we researched which companies made good impressions on us. The five companies that came up as the most impressive were Starbucks, Oriental Land, Nintendo, Apple, and Patagonia. The analysis revealed that all of the companies have developed a clear vision. It is thought that a clear vision and the creation of touch points based on a thorough vision have led to the formation of an image. The next step was to evaluate Forest Notes. From the evaluation, it became clear that although Forest Notes has a high level of performance, it is difficult to create value for users because it does not convey its purpose and intent. We need to clarify our targets and clarify the meaning of Forest Notes. In the future, we will decide on the target, think about UX, and propose a new Forest Notes.

In order to deal with complex social issues and/or to create innovative designs that create new values, the co-creation approach, in which not only designers but also various disciplines and stakeholders are involved in the design process and create together, is gaining attention. The research field of co-creation dialogue scenes and creative processes has not yet matured, and there is still room for further research on the design of co-creation dialogue scenes. There is still little knowledge analyzed from actual co-creation scenes about what kind of dialogue styles occur and how design requirements are defined. In this study, we will conduct a workshop that includes elements of co-creation, and analyze the processes of three different teams in order to see the patterns of ideas in the team processes. From the analysis of a case study of a UX-based workshop that included prototyping, the characteristics of the team’s conception patterns are reported as results.

Design is changing. The object of design has changed from users and products to customers and services, from the interface of products to the touch points of the journey, and from the interaction of digital products to activities in the digital world. In the past, the division of labor in which the designer made the design first, and then provided the design to the user after completion, will become a continuous co-creation activity between the customer and the designer in the future.Scenario was originally a design tool, but now it has become a design object. This article explores how to carry out human-centered, Scenario-Oriented Activity Design through a multi-perspective co-creation process under such changes.This paper proposes a framework for connecting activities and scenarios with narratives. The visual narrative combined with the guidance method of switching from multiple perspectives allows the co-creation team to generate multiple empathy, and conduct usage activities, design activities, and facilitating activities at the same time. This paper also proposes a co-creative narrative guiding structure O-S-M-C that echoes the dynamic sequence of activity theory to assist the design of innovative activities. This paper also illustrates with practical examples.

Card sorting is a popular way for creating website information architectures based on users’ mental models. This paper explores the effect of participants’ self-efficacy on card sorting results. A two-phase study was carried out. The first phase involved 40 participants rating their self-efficacy on a standardized scale, followed by an open card sort experiment. The median self-efficacy score was used to split the open card sort data into two groups: one for low and one for high participants’ self-efficacy. These two datasets were analyzed following state-of-the-art techniques for open card sort data analysis, which resulted in two information architectures for the eshop. In the second phase, two functional prototypes were first created for the eshop, one for each information architecture of the first phase. Subsequently, 30 participants interacted with both prototypes in a user testing study. This paper found that users interacting with the information architecture produced by open card sort participants with low self-efficacy made statistically significantly more correct first clicks, significantly less time to find content items, rated the tasks as significantly easier, and provided higher perceived usability ratings compared to when they interacted with the information architecture produced by users with high self-efficacy.

With the spread of “ICT tools” such as smartphones, which allow us to connect to the Internet anytime, anywhere and obtain information, the number of things we can do easily has increased and our lives have become more convenient. On the other hand, I felt that there are many things that we no longer value because the number of things that frustrate us when we can't do something, but only make us feel “normal” when we can, has increased.Therefore, this research aims to build a model that includes experiences and emotions related to ICT tools, referring to” the Kano model”, which is a concept that models the quality required by customers. Based on this model, the goal of this research is to provide a means to offer new attractions, and to find a way to create value in experiences that have become commonplace over time.As an indicator for building a model, we will conduct a factor analysis of “what is taken for granted” and “what is attractive” in ICT tools and applications used in conjunction with them. In this paper, I introduce the survey I conducted as a preliminary step to gather information.

In recent years, social media has been used by many businesses, governments and individuals. Social media is helping to build new relationships as well as strengthen existing ones. Many individuals are said to exist merely as searchers of information. However, including anonymous engagement behaviors such as “likes”, they are also considered to be expressing their intentions. We call them Lurker, but can we use Lurker's principles of action to revitalize the local community?This paper presents the results of an experiment featuring a smart phone social media application (app) intended to incentivize communication during certain health behavior, namely walking, among participating users in Japan, through a non-monetary point system. Our research question is to clarify the point system that have no economic value activate reciprocal motivation and communication by making connections between individuals visible in a non-anonymous manner. Upon analysis of the data obtained, two main findings were revealed. First, over time, the non-anonymous point system where points have no economic value did not effectively activate communication among participants given the experimental conditions. However, when the rules and goals for using points are clearly defined, when point use targets not only individuals but also places or events (as will be explained), and when approval is anonymously and easy to express and feedback easy to obtain, app use becomes sustainable.

Discussions in the comment sections of news articles are often characterized by highly one-sided arguments. One reason for this is that users primarily consume information that fit into their worldview and consequently argue from their echo chamber when responding to a comment. In this paper we introduce a new approach to comment recommendation. To this end, we present a model that makes recommendations based on a specific comment the user is interested in. These recommendations provide the user with alternative related comments and thereby broaden the perspective of the user before reacting to the specific comment that was originally selected. This is in contrast to previous work that tries to recommend comments based on the interests and previous behavior of the user and therefore fueling the filter bubble by providing information that fit into the worldview of the user.

When users unknowingly interact with false information online, they may be susceptible to the influence of misinformation. Using a fact-checker to analyze whether the information presented is accurate or misleading can help users identify false information. The present study examined two different methods: use of a correction or warning, presented by a fact-checker, to identify which is more effective in reducing misinformation. One hundred and twenty-four participants were recruited from MTurk and Introductory Psychology courses to participate in the study. Participants were asked to read short stories, followed by statements that are related to the short stories (e.g., media posts about the short stories) that were or were not verified by a fact-checker. Then, participants were asked to answer questions related to the original short story to measure their memory of the information as well as the number of references to the misinformation. At the end of the study, participants were asked to rate their level of trust in online information sources and the fact-checker used in the present study, which always provided accurate information. Results showed that participants used a fact-checker about 70% of the time when one was made available to them. Having a choice to use a fact-checker increased participants’ accuracy scores on a memory check test, and the presence of a fact-checker reduced the number of references to misinformation.

Social media is popular for us to share some news; however, it is easy for us to receive much fake news and believe them because of its simplicity. A new model is proposed for simulating a cyber-physical system preventing fake news with humans and agents by expanding the opinion sharing model (OSM), and this paper proposes a decision-supporting system based on the model for users to avoid fake news. The experiments investigate the performance of the proposed system in social network simulation based on Twitter. The experimental results show that: (1) the proposed system performed the same simulation in the OSM’s situation. (2) The user should inform the received information to the agents straightforward for sharing correct information. (3) The proposed system enabled the agents to suggest the opponent opinion of fake news to the users when they had shared the fake news in the simulation based on Twitter posts.

In this paper, we proposed a robust finger tap gesture recognition method and examined the feedback function when operating information devices using finger tap gestures. A finger tap gesture recognition method using hall sensors and gyro sensors achieved a high recognition rate without causing false detection. However, when operating information devices with finger tap gestures, there are the following two problems. The first is that it is recognized as a gesture different from the intended gesture, and the second is that the user’s subjective gesture success or failure differs from the actual gesture success or failure. If the above phenomenon occurs, the user cannot operate the information device smoothly. In this paper, we aimed to make it possible for the user to quickly grasp the state of the information device and take appropriate actions by presenting the user with immediate feedback according to the type of gesture immediately after the successful gesture. As for the types of immediate feedback, tactile feedback and sound feedback were prepared and compared those feedback condition. As a result, it was found that by giving immediate feedback, the user can properly grasp the state of the information device and quickly per-form appropriate operations. Furthermore, when comparing tactile feedback and sound feedback, the operational performance tended to be higher for tactile feedback, and the subjective evaluation tended to be higher for sound feedback.

Crowdsourcing techniques have been developed over the past decade to leverage the ‘wisdom of crowds’ to solve real-world problems and human intelligence tasks. An example of such a task is fact-checking, that asks workers to check whether the shown claim is true or not. Fact-checking tasks are used in many applications such as services to identify fake news. This context motivates us to investigate a crowdsourcing-based framework to find convincing proofs for fact-checking. This study investigates a good crowdsourcing strategy to obtain convincing proofs with evidence. We focus on an iterative workflow in which workers improve the proofs provided by other crowd workers. In this study, we show the results of our experiment, in which we compare the results of two conditions, by which we see the effects of the diversification of shown evidence and proofs. The experimental results with real-world workers show that showing diverse evidence and proofs to crowd workers in the iterative workflow helps them develop more convincing proofs.

This paper developed a voice communication system, the Overheard Text Map (OTM), which displays the frequent words of a conversation in a virtual space. Participants who engage in voice communication using the OTM can create conversation rooms. They may move freely among the rooms, if they mutually agree to do so, holding internal departmental meetings, group discussions at seminars, poster sessions, and informal gatherings, for example. The OTM displays frequent words in the current conversation to the participants outside the corresponding room using a word cloud. The word cloud selects multiple words with a high frequency of occurrence in the text data of conversations and displays them in a size corresponding to their frequency. In this way, participants can obtain an overview of the conversation in the room without joining it. Therefore, it is expected that the participants will find it easier to choose and join a room with conversations that match what they want to talk about. In the experiment, participants watched the word clouds and chose an appropriate room where participants were having a conversation that matched what they wanted to talk about. The results showed that word clouds created based on discussions are useful for people who want to join an appropriate conversation room.

This paper takes the visual design of tea culture in three different regions of China as examples, compares the perceptual impression brought to people by different cultural atmosphere and environmental background in the three regions, and applies it to the visual design related to tea culture. Questionnaire survey was used to analyze the perceptual impression differences between local residents and foreigners in these three regions, and based on the survey results, suggestions were put forward to improve the impression differences between the two sides, and optimization plans were put forward to facilitate intercultural communication. A survey and analysis of perceptual impressions of three regions of China from the perspective of local residents has been published in HCII2020. As an extension of this project, this paper obtains some effective information from the survey of how foreigners feel about different tea cultures and regional image of other countries from the perspective of foreigners. Finally, the above survey and analysis results of perceptual impression from the three regions are integrated into the visual design proposals of tea culture in the three regions. Through the perspective of local residents and foreigners, fully understand the feelings and ideas of both sides, and realize the effective conversion of design language and cultural transmission and communication.

One of the top causes of adverse drug effects is the mislabeling and misreading of instructions or warnings on medical labels. In addition to miscomprehension of these labels, label information may be missed or seen incorrectly due to a lack of sufficient attention and visual processing. Currently, there is little consistency in prescription medical labels across providers, with warning labels containing either icons, text, or a combination of both. The present study examined how the design configuration of iconography and text on medical labels influences attention to specific label elements. A flicker task was used in two experiments in which a set of medical labels were presented on a display. Participants were required to detect and identify changes in a label’s icon, text, or both. Overall, the results indicate that viewers tend to focus attention on icons rather than text, and that label information is more likely to be missed on labels containing both icon and text information compared to labels with a single type of information. We discuss how change detection in the current study relates to design considerations for prescription medical warning labels.

In recent years, the number of Internet users has been increasing every year. Influenced by the demand for stay-homes in Corona, the current situation is that the Internet is becoming even more popular. In particular, the use of social networking services has increased, indicating that the spread of social networking services among the younger generation is remarkable. From the usage of social networking services, it can be seen that Instagram is the media that shows a large difference among the usage groups. In addition, Instagram is highly effective in appealing to visual information, and is said to be suitable for marketing cosmetics and clothing. (The cosmetics industry has been cited as an industry that has seen a drop in sales in the Corona disaster. Therefore, the cosmetics industry needs to change its marketing methods and aim for recovery in the market. Therefore, this study will focus on the cosmetics industry and discuss effective marketing methods on Instagram. First, we will analyze the characteristics of the cosmetics industry and Instagram users to find common points. Next, we will analyze their behavior on the Internet, focusing on the common point of “fashion-conscious people”. Finally, we will examine what kinds of posts on Instagram are most likely to appeal to customers.

In Japan, there are more right-handed people than left-handed people. For this reason, most of the things in our daily lives are designed with right-handed people in mind. This has led to many inconveniences that left-handed people experience in their daily lives. In spite of the fact that writing is a basic activity that is required from an early age and is performed many times in daily life, the inconvenience felt by left-handed calligraphers is much greater than that of right-handed calligraphers. In this study, we examined the inconvenience felt by left-handed calligraphers when writing Japanese. Therefore, we conducted a meta-analysis of the inconveniences felt by left-handed calligraphers when writing to find out what elements of calligraphy are responsible for the inconveniences they feel. The purpose of this study is to clarify the writing Japanese characteristics of left-handed calligraphers and to summarize them in a form that can be easily understood by people other than left-handers.

Objective: To provide ideas and schemes for the emotional design of mobile input method skin. Methods: The emotional experience evaluation experiment was designed according to the selected representative skin samples of input method, so as to obtain the emotional response data of each sample under different emotional dimensions. Conclusion: through the analysis of experimental data and the comparison of different sample design elements, the suggestions of skin design optimization of mobile input method based on emotional experience are put forward.

A situation map shows the dynamic changes of the environment within a specific space and time in the form of graphics, which can help users effectively understand the current situation and predict the future situation from multi-dimensional and massive information. It is an essential tool for users to make decisions in a complex information system. However, the current situation map interface has some problems, such as poor visibility, difficulty in interaction, etc., which has a particular impact on the user’s performance of situation awareness and the efficiency in completing tasks.In order to improve the current problems of the situation map interface, this study hopes to optimize the design of the situation map interface based on the cognitive characteristics of users. A large number of eye movement data of users in the situation map were collected and analyzed to. After analyzing the time series data of eye movement coordinates, the duration of fixation point entering the target area of interest (AOI) for the first time, eye movement speed and other eye movement characteristic indicators, as well as the scanning path chart, it is concluded that the differences of users’ eye movement behaviors were mainly manifested in three aspects. They are the differences in visual search strategy, target positioning speed and accuracy, and decision-making speed and accuracy.Then, according to the differences in cognitive characteristics such as attention distribution mechanism and information processing efficiency reflected by the differences in users’ eye movement behaviors, the cognitive types of users are summarized as blind cognition, purpose cognition, learning cognition, and memory cognition. Based on the characteristics of the above four cognitive types, the situation map design elements are extracted and sorted out as the criteria for subsequent interface optimization. The optimization design scheme of the interface elements of the situation map is proposed to help users improve their situation awareness level, information identification efficiency, and task operation efficiency.

In this paper, we proposed a method to detect and improve bottlenecks in the data flow of IoT systems. Various IoT devices such as sensors and actuators are used in IoT systems, and millions of data flow through the edge nodes to be processed. Data exchange between edge routers is processed in buffers in sorted order of the event-driven flow. However, because buffers in edge routers are limited, link interference and power instability always reduce the latency of the system. Even a small misalignment in data flow may cause minor incidents that will later cause a chain of breakdown. In this study, we model the data flow with program nets to capture the stagnation of data tokens in order to detect bottlenecks. The data flow is modeled with Program net, and we can visualize the flow of data represented by tokens. We also proposed a mitigation method to tackle the bottleneck problem. Then, we demonstrate the effectiveness of our approach by quantitative evaluation. The evaluation result showed that the proposed method could detect bottlenecks in IoT systems and reduce the buffer to below the 80% of the threshold value.

University dropout is a concern for educational institutions since it directly impacts management and academic results, as well as being directly related to social problems. The literature points out that analyzing this phenomenon is a positive factor for developing programs to combat dropout, in addition to planning interventional actions and academic monitoring, making it possible to identify students at risk of dropout through techniques that use Machine Learning, for example. This paper presents a panoramic study of a public university, in which the school data were analyzed and classified using Machine Learning. The analysis of the data allowed to obtain an overview of the dropout data of the studied university. In addition, the main stakeholders were interviewed to report their main difficulties to know statistics about dropout. Considering these different data sources, we created digital reports to professors, chiefs and academic assistants, with information and statistics to assist university managers in decision-making related. These reports were validated by stakeholders and we hope that the next decisions can minimize any problems related to mental health, thus improving the quality of life of students, as well as their academic trajectory.

A basic concept of loan is reconsidered all over the world by the new BIS regulations. However, many people in Latin America still have a vague way of thinking about loans. It is due to the global recession. As a result, companies have not been able to recover their manufacturing costs. However, a large potential market has been formed in Latin America. Therefore, the challenge for companies is how to formulate product strategies that can meet the needs of the market. Therefore, in this study, we create a classification model of whether customers will default or not. In addition, we explore the characteristics of the default customers. Propose a sales strategy for the product based on these characteristics. This would help companies to improve their financing problems and secure profits. In this study, we compare the accuracy of Logistic Regression, Random Forest and XGBoost. Since the data handled in this study were unbalanced data, data expansion by Synthetic Minority Over-sampling Technique (SMOTE) was effective. Finally, we analyze analyzes what variables contribute to the model by using SHapley Additive exPlanations (SHAP). From this analysis result, we will explore the characteristics of what kind of person is the loan unpaid customers. The variables with the highest contribution were the type of vehicle purchased, the area where the customer lives, and credit information. We propose sales strategy by focusing on the variables that are significant to the model.

In Japan, birth rates are declining year by year. If this goes on, half of municipalities will disappear. Recently, there have been many studies on fertility using TFR as a benchmark for municipal unit data. However, when considering the municipal level, it is not sufficient to focus only on the TFR in investigating the reason for the declining birthrate. In this paper, we conducted an analysis of fertility decline by focusing on TFR and women moving in and moving out of regions. We used OLS regression that do not take into account regional differences and Geographically Weighted Regression (GWR) which allows to include regional differences. We could infer that low income and women’s social advancement, which are generally considered to be factors in declining fertility, do not have much of an impact from the results. We also found that there are regional disparities in TFR that cannot be explained by the variables incorporated in this study, and regional disparities were a trend of west high and east low. In addition, when we looked at the policies of regions that have been successful in maintaining their populations, we also found that there are common steps in policies that are successful in maintaining population.

The level of soccer in Japan is getting higher and higher. This is due to the fact that more and more players belong to overseas teams. However, if this trend continues, there is a possibility that the level of soccer in Japan will decline again. One of the reasons why j-league players are not selected for the national team is that there are few objective indicators of player characteristics, and they are easily influenced by the judgment of their team’s coaches and managers. Therefore, the purpose of this paper is to analyze and visualize the characteristics of players. In this study, the analysis was conducted on midfielder players in the J1 League. The reason why we chose the position of midfielder among many positions is that it plays an important factor in both offense and defense. The analysis was initially done by principal component analysis to create new variables to understand the characteristics of the players. Then, a hierarchical cluster analysis was conducted on the principal component scores to divide the players into several groups and identify their characteristics. As a result, we were able to classify them into seven distinctive groups.

Visualisations offer a variety of novel ways to depict data to a wider range of users. Moreover, they provide the ability to transform raw data into intuitive visual mechanisms for communication. Despite the developments in visualisation techniques, an area of depiction that has struggled to advance is uncertainty. The visualisation of uncertainty offers an additional dimension for the data by presenting confidence and error rates. Whilst nearly all predictive data sets visualised contain uncertainties, there is still little impulse to actively represent uncertainty. A growing area of interest in the visualisation world is the field of aesthetics; the authors ask the question ‘could aesthetics be applied to address the issues surrounding visualising uncertainty’. This paper reports on the design and delivery of a study to evaluate the effectiveness of aesthetics for the depiction of uncertainty. In particular, the evaluation of how to practically determine how we assess the influence of aesthetic dimensions for the presentation of uncertainty. The paper reports on the strategies employed in this study to assess user’s decision around aesthetic designs, whilst determining what aesthetic combinations elicit the most uncertain visual representation. The findings show that certain aesthetic combinations in a line graph visualisation portrayed a higher level of uncertainty than others and that particular combinations triggered affective responses based on how the visualisation influenced/impacted a participant. In detail, how the textured line characteristics can be displayed aesthetically (combined with either emphasis or scale) to encourage optimal user experiences of uncertainty in a diverse participant group. The paper highlights how a user’s decision on which texture was most uncertain can be overturned when presented with varying levels of emphasis and scale. In summary, this paper contributes to a more in-depth understanding of how to design for and evaluate aesthetic uncertainty visualisations that encourage interaction with the data.

Software systems and components increasingly rely on machine learning methods such as Artificial Neural Networks (ANNs) to provide intelligent functionality. Therefore, software developers and machine learning users should have a basic understanding of such methods. However, since ANNs are complex and thus challenging to grasp, novel visualization approaches can contribute to a better comprehension. We conducted an online survey to identify use cases and requirements for visualizing ANNs. Based on our results we designed and implemented an ANN visualization in virtual reality (VR) specifically targeted at machine learning users. Our approach is particularly suitable for teaching purposes and machine learning novices or non-experts who want to get an impression of the general functionality of neural networks.

Open source software (OSS) are used under the various situations, because OSS are useful for many users to make cost reduction, standardization, and quick delivery. While OSS have many advantages, it is difficult for us to quantitatively grasp the progress of development such as general software development because OSS are developed by many different people around the world. In general software development, Earned Value Management (EVM) is often used to quantitatively evaluate the progress of a project. However, it is difficult to apply EVM directly in terms of the characteristic of the open source project. Therefore, EVM in open source projects has not been sufficiently researched.In this paper, we apply the progress data of open source projects to EVM. We also try to derive the bullseye chart by using the Cost Performance Index (CPI) and Schedule Performance Index (SPI) known as the indexes of EVM. Also, we apply the derivation method discussed in this paper to actual open source project data in order to quantitatively evaluate the project.

At present, there are various software services by using the cloud computing. In particular, the edge computing expanded from the cloud computing is embedded in various situation because of the avoidance of whole system down. Also, the technologies of cloud services based on edge computing and 5G are very important to keep our convenient lifestyles. The appropriate control of the software faults detected in OSS project will directly relate to the quality, reliability, and cost. In particular, the fault correction time is very important factor in order to keep the edge computing service. We focus on the visualization of the estimation results of fault correction time for the assessment of operation performance of edge computing open source software. Then, we discuss the estimation method of fault correction time based on the characteristics of several components by using the deep leaning. We use the deep learning in order to estimate the fault correction time. In particular, we discuss the characteristics of fault trend by using the three dimensional graphs as the visualization of fault big data. Thereby, we can show the recognizability of the proposed method for fault big scale data based on deep learning from the standpoint of edge open source software. In particular, this paper analyzes the fault correction time from the standpoint of the characteristics in the fault content for the actual data sets. Then, we make a visualization based on three dimensional graph by using the estimation method based on deep learning. Moreover, we discuss the estimation results obtained from the three dimensional graphs. Furthermore, we show several numerical examples based on the proposed estimation method by using the actual fault big data. We analyze the fault big data in terms of the fault correction time in OSS component of edge computing in cloud computing in OpenStack. We can obtain the fault correction times from several characteristics of the factor in the bug tracking system. In this paper, we discuss two kinds of characteristics from the bug tracking system.

Power harassment has become a problem in Japan recently. However, it has been found that reading judicial precedents is one of the ways to prevent it. In this paper, in order to promote the reading of judicial precedents, we visualized the relationships between people in judicial precedents, which are not easy for non-experts to read. We first extracted the words from the text of judicial precedents that represent people using morphological analysis. Next, we then extracted information about the relationship between the persons using dependency analysis. We then determined the direction of the extracted relationship. Finally, based on the automatically extracted relations between the persons, we visualized the structure of the case as relationship charts and fishbone diagrams. To confirm the usefulness of the proposed diagrams in reading judicial precedents, we conducted an evaluation experiment using both judicial precedents and diagrams on six Tokyo University of Science students. The results suggest that diagrams make it easier to read judicial precedents.

In mechanics, it is important to understand the relationships between forces acting on objects. To help learners understand these relationships, a number of mechanics-based learning support systems have been developed. Many of these systems deal with drawing problems. Drawing problems require learners to draw the forces acting on objects in a given physical system using arrows. However, when the relationships between forces are complicated, learners may get stuck. It has been shown that providing auxiliary problems to learners who get stuck can be effective. An auxiliary problem is one that helps the learner understand the original problem. When a learner is presented with an auxiliary problem, they can solve that problem and use errors noticed in it to assist in solving the original problem as well. However, learning by solving auxiliary problems may confuse learners if they are not given ones that are appropriate to the original problem. In order to create appropriate auxiliary problems, it is necessary to create them using consistent rules. We have been working on the automatic generation of auxiliary problems for mechanics. Specifically, based on Mizoguchi et al.’s causal reasoning theory of force and motion, we investigated how to generate problems with consistent deletion. In this paper, we elaborate the rules for generating auxiliary problems, aiming for the automatic generation of them by the system.

This paper compares the category creation process during a user study experiment in a cognitive immersive sensemaking environment between an analog and a digital sensemaking tool. The digital sensemaking tool is situated in an immersive environment, comprised of a global view, a personal view, and verbal and gestural technology that allows users to be fully engaged in their tasks. The user study (n = 26) examined the words used in both analog and digital tools, and compared the frequency of words generated by users, as well as the representativeness of categories to the materials given to participants. The sensemaking tool in this experiment is a novel brainstorming tool that utilizes interactive technologies which allow participants to seamlessly create knowledge artifacts like sticky notes and categories, while also leveraging the affordances of digital technology to help streamline sophisticated cognitive processes, like sorting and deciding the most salient information and collaborating with group members.We found that while frequency of words differed little between tools, users were more conservative in their word choices with the digital sensemaking tool, making their choices more representative of the source material.

In the context of learning, the effectiveness of learning-by-teaching (LbT) is widely recognized. LbT is a method through which learners deepen their understanding by teaching others what they have learned. In order to realize LbT, it is necessary to have the behavior of the teachable person, such as the knowledge of other and an attitude towards receiving instruction, as well as the existence of the teachable presence. One technology for approaching this challenge is called a teachable agent. A teachable agent is an agent that behaves as if it is learning what is taught by the learner. Another effective learning method is error-visualization. Error-visualization is a feedback-based approach to simulating the answers by the learner as (abnormal) behavior. However, no modeling methods have been proposed that combine teachable agents with error-visualization. In this paper, we propose teachable agent modeling for error-visualization (TAME) as a teachable agent modeling method that aims to combine teachable agent with error-visualization. As a case study, we realize a teachable agent using the TAME modeling method based on a conventional learning support system called Monsakun.

The advances of aviation technology continue to boost the performance of fighter aircrafts and to complicate future sky battlefields, which continually add more and more information that must be presented to the pilot via the cockpit interface, significantly increasing his/her cognitive workload. This study analyzes the evolution of contemporary in-cockpit display interface of warplanes, identifies the general rules of the interface design and looks ahead to future development trends. By doing so, this study brings forward principles of cockpit display interface design from the perspective of visual attention mechanism and tests their effectiveness and feasibility via comparative experiments using simplified prototypes.

Learning from code written by other programmers is one of the most important ways of learning how to program. However, reading the code of a skilled programmer can be difficult for a beginner. Put differently, learning how to program can be challenging when the learners have different levels of programming proficiency. To lessen these difficulties, it is necessary to present model code that corresponds to the proficiency level of the learner. However, since proficiency levels in programming may vary by learner, preparing model code matching the proficiency level of every possible learner in advance may not always be practical. Therefore, we propose a platform for sharing knowledge among various learners participating in a given lecture. Functionality for sharing code alone may be insufficient for presenting code appropriate to the level of a given learner. Therefore, we also propose code quality indicators for understanding the degree of proximity in proficiency between a learner and a given programmer whose code is being used as a model. To this end, in this paper, we propose a platform with functionality for sharing, evaluating, and ranking written code. In addition, in order to understand the relationship between code written by other programmers and the behavior of the code at runtime, we propose a platform that involves programming a robot in order to allow the learner to visualize the behavior of the code as movement of the robot.

It is well known that nonverbal information plays the important role for smooth communication. On the other hand, it is also suggested that limiting transmitted nonverbal information leads to accurate comprehension. Further, it is shown that the face-to-face environment and the video chat environment have different influences on the talkers. However, it has not been verified that influences of visual nonverbal information in interactive communication on the feeling/degree of transmission in a video chat environment. Therefore, in this research, we try to verify the influence of varied communication environments on the feeling/degree of transmission and speech/body motion of the talkers in interactive communication by natural dialogue. In communication experiment, we prepared three experimental conditions which are controlled visual nonverbal information by using the dimming glass. As the result of experiment, it was shown that the suppression of the visual nonverbal information causes the decrease in the feeling of transmission and the head motion and, the increase in the degree of transmission and the arm motion. Furthermore, in the environment that can only be seen participants partner’s body motion, there is a possibility that the feeling of transmission is worse, and the degree of transmission is most excellent in three experimental conditions. Secondly, the video chat environment was compared with the face-to-face environment. As the results of experiment, this condition is similar to the environment that participants can only be seen partner’s physical motion. Furthermore, it was suggested that this environment may affect the increase the degree of transmission, the increase in the arm motion, and the decrease in the utterance rate.

Reading gives readers intellectual stimuli, elicits their imagination and creativity, and expands their inner world. We introduce the concept to postulate that reading is communication between a reader and a book. An idea is to change a book into a reactive entity and to achieve interactions between a reader and a book. We have introduced a mechanism to feedback a reading note as a response from a book to a reader’s gaze information that the reader generates during reading. Reader’s gaze information generated during reading shows his/her mind about the book. The goal of this study is to build an automatic reading notes creation system that automatically generates reading notes based on gaze information that a reader naturally generates during reading. We conducted experiments to measure a subject’s gaze coordinate data, and to verify whether we could identify eye movements for specific four reading patterns through the analysis of the acquired data. As the result, we have confirmed it possible to identify a reader’s reading patterns from the change of gaze information.

Recently, the demand for IT human resources has increased. Therefore, the expansion of programming education should be considered to strengthen the supply of it. This study aimed to propose debugging learning support for novice programmers using experts’ gaze behavior. First, we gave feedback to proficient users on their gazing behavior during program debugging and interviewed them about their cognitive processes. Based on the results, we developed a cognitive process model of expert debugging. However, most of the visualized information was based on gaze transitions, and it was difficult to see the characteristics of the cognitive process. This study helped to improve the previously proposed model and developed one that focuses more on the cognitive process during program debugging. Data from students with little programming experience were collected and compared with the cognitive process model of programming experts. This enabled the identification of the characteristics of the program debugging process of non-experts.