Streaming services repetitively provide similar kinds of music, and listeners might get tired of them quickly. This is one of the serious problems for streaming services today.

is developed with repetition, and it depends on personal preference. Therefore, development depends on the time spans of the repetition and personal preferences when people listen to the same music over days. This study conducts an experiment that the participants repetitively listen to one music piece 294 times for seven days in a row to observe development. We measured the level as the reactional factor of the failure to keep the concentration and motivation of listening. As a result, the concentration decreased in the short-term, whereas the motivation decreased in the long-term. Therefore, we could distinguish the state of by the length of the time span. In addition, compared to repetitive listening with a day as the short-term, repetitive listening every day in a week as the long-term had an equal or slightly higher power to generate , but there is a weak correlation between and preference for a music piece. In conclusion, the results showed that the amount of repetition had a stronger effect than personal preference for music, and people may get bored even with their favorite music when they listen too many times. Moreover, the behavior of the low-frequency alpha wave in the brain had only a weak relationship to the amount of listening within a day, not in the week.

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With the evolution and spread of information technologies including Web, the amount of information that users can obtain has dramatically increased. Huge quantities of information have made it difficult for users to reach their desired information. In order to address this problem, various information recommendation systems including cooperative filtering have studied and developed with certain results. Many of traditional studies on information recommendation provide a method to statistically determine, based on the user's preferences and behavioral history, the right information to recommend. Because the user's request depends on their situation as well, there are also information recommendation studies that take the user context into consideration. These traditional studies, however, aim at recommending highly satisfactory information in a one-time or small number of uses of a system or service, and never take it into account that the user would feel tired of the same system or service after they have used it many times over. In reality, if the user can obtain information to their preference, they would feel very satisfied with it at first, however, if they are only presented with similar information every time, they may eventually get tired of the system and cease to use it. Consequently, in order to realize an information recommendation system that the user wants to continue to use, you need consideration of a human nature of being tired of the same thing, as well as interaction design for information recommendation that leverages its characteristics. This study has modeled the human nature of being tired of the same thing and enabled the measurement of the degree of such . Also, the study has implemented an information recommendation system that has features to (1) visualize the degree of the user's and (2) recommend information that can reduce it. Then, an evaluation experiment was conducted using a system developed. The result shows that an information recommendation system proposed in this study can get the user less bored and more satisfied when used continuously. In addition, it enables the user to make various choices even in a limited content. These results suggest that both information recommendation based on a Kansei model of human and interaction that visualizes the degree of the user's and makes them conscious of it work well for their continuous use of the system.

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This paper presents the major outcomes of a comparative survey on aesthetic of Mobile Phone (MP) in the contexts of Japanese and Iranian university students that is the second phase of a research experimentally founded on an inverse approach to product aesthetic durability, the particular indication of product aesthetic sustainability. Based on the results of first phase of research shown in the last paper, MP and the youth are decided as the object and subject age range for the research fieldwork on product aesthetic , the opposite of product aesthetic durability. In this survey, the required data are gathered through the definite questionnaire to investigate the users' actual experiences of MP aesthetic . The survey aims to extract, itemize and classify the causal elements and factors of product aesthetic in terms of using MP in Japan and Iran to finally compare it between two countries' contexts.

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This study aimed to demonstrate the empirical distinctiveness of

at work and work engagement in relation to their potential antecedents (job demands and job resources) and consequences (psychological distress and turnover intention) based on the Job Demands-Resources model. A three-wave longitudinal survey was conducted among registered monitors of an Internet survey company in Japan. The questionnaire included scales for at work, work engagement, psychological distress, and turnover intention as well as participants’ job characteristics and demographic variables. The hypothesized model was evaluated via structural equation modeling with 1,019 participants who were employed full-time. As expected, at work was negatively associated with quantitative job demands and job resources and positively associated with psychological distress and turnover intention. In contrast, work engagement was positively associated with job resources and negatively associated with turnover intention. Thus, at work and work engagement had different potential antecedents and were inversely related to employee well-being and organizational outcomes. However, contrary to expectations, qualitative job demands were not significantly associated with at work. Further investigation is needed to understand the relationship between and qualitative job demands, which require sustained cognitive load and the use of higher skills.

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Objectives: The current study aimed to validate the Japanese version of the Dutch

Scale (DUBS-J), a new scale that comprehensively assesses employees' emotional, cognitive, and behavioral responses to low-stimulus work situations.

Methods: The translated and back-translated DUBS was administered via an internet survey to 1358 Japanese employees from various occupations. Confirmatory factor analysis (CFA) was conducted to evaluate factorial validity. In order to evaluate discriminant validity with other work-related, well-being constructs, CFA was conducted, and the square root of average variance extracted (AVE) for the DUBS-J and the square of the inter-construct correlations were compared. Construct validity was evaluated based on the correlation coefficients between

at work on the one hand and potential antecedents and consequences on the other hand.

Results: Confirmatory factor analysis supported the expected one-factor model. CFA and AVE supported the discriminant validity of DUBS-J with work engagement, workaholism, and job satisfaction. Construct validity was generally supported by expected correlations of

at work with possible antecedents and consequences. Internal consistency was confirmed with Cronbach's alpha coefficient = .88, and the results of principal component analysis (PCA). Test-retest reliability was confirmed with intraclass correlation coefficients = .62.

Conclusion: The current study confirmed that DUBS-J is an adequate measure of

at work that can be used in the Japanese context.

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This paper is concerned with an analytical research on product aesthetic durability that is considered as the particular indication of the broad concept of product aesthetic sustainabiliry. As aesthetic is the opposite of aesthetic durability, the research goes into a comparative fieldwork on product aesthetic to inversely approach product aesthetic durability. Indeed, this paper prefaces the fieldwork whose major outcomes will appear in the two following papers. So, it generally reviews the whole story, backgrounds, approaches and plans of the research, and specially introduces the process and results of an exploratory inquiry on product replacement before the products breakdown as the first phase of the fieldwork in detail. The results of this exploratory inquiry firstly illustrate the role of in product replacement and finally lead us to decide the object and subject age group for the next phases of the fieldwork.

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This paper presents the third phase of an analytical research on product aesthetic sustainability that its outline has been introduced in the first paper of these serial articles generally entitled 'An Inverse Approach to Product Aesthetic Durability'. The focus of research is on product aesthetic , the opposite of product aesthetic durability. The individuals' actual experience of product aesthetic has been surveyed during the second phase of research. But this third phase of research aims at experimenting with the subjects' appraisal of of the objects in relation to the objects' form-structural characters. The choice of samples of two groups of mobile phone used in Japan and Iran and the form-structural variables are based on the results of the second phase of research presented in the last paper. Finally, it compares the derived form-structural patterns and their rates of appraised by the Japanese and Iranian subjects regarding the same samples.

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English rhythm instruction materials (RIM) encourage users to learn English rhythms. However, when one repeats the same lesson many times, it is typical to become bored. What happens to brain waves in the event of - do some brain waves change? To clarify this issue, we acquired electroencephalograms (EEG) of learners' brain waves as they repeatedly completed the same RIM lesson. We also asked them to raise their hands when they felt bored. Time-frequency analysis using fast Fourier transforms of learners' EEGs showed that the power of their α (8-12 Hz), β (8-30 Hz), and γ (30-50 Hz) waves first held constant, then decreased at many electrode regions over the course of the lesson. After the decreases in EEG power, the subjects raised their hands to indicate . On the other hand, the power in the θ waves (4-8 Hz) did not change. These results suggest that the decrease in α, β, and γ power across wide regions of the skull can serve as signs of among learners.

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We get bored when we have nothing to do. The psychological definition of

is the aversive state of wanting, but being unable, to engage in satisfying activity. To avoid feeling , humans left in an empty room actively receive aversive shocks. Here, we found that mice also received aversive air puff stimuli more frequently when they were placed in an empty cage than in an enriched cage with toys. Some mice exhibited an addiction-like state in which they received air puffs more than once per second. This self-stimulation increased and decreased by activation and inactivation of the insular cortex, which is related with in humans, respectively. Next, we recorded neural activities from the insular cortex. Using support vector machine, we can predict the timing of self-stimulation with spiking activity of insular cortical neurons. To investigate the neural mechanism of receiving aversive air puff stimuli, we recorded dopamine signals of the ventrolateral striatum that expressed a dopamine sensor. Dopamine levels increased before receiving air puffs actively, while decreasing after receiving air puffs. Finally, an μ-opioid receptor antagonist decreased self-stimulation including the addiction-like behavior. This study suggests that the state of converts aversive stimuli to rewards and will provide clinical insights into addiction and self-injury.

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We propose a robot behavior generation scheme that generates behaviors based on senses of “curiosity” and “

,” to create a companion robot named SELF with which humans do not get bored. The scheme was developed using a simple but unique simulation environment. A red ball and a blue ball were displayed on a computer; the human subject moved the red ball. First, the impressions of various motions and actions of the robot were examined. The actions at moderate speed create agreeable impressions. Based on natural interpersonal interaction patterns, the actions that the robot is expected to generate are classified into four types: “following action,” “fleeing action,” “no interferential action,” and “no action.” We analyzed humans’ impressions of the behaviors of the robot generated by switching the four basic actions at moderate speed. Three types of information transfer efficiency characterized these behaviors. We proposed the behavior generation scheme for SELF. The autonomous learning capability of SELF was realized by updating this conditional probability. Using the developed scheme, SELF can display curiosity and resembling that seen in animals, including humans. Lastly, impressions of the robot behaviors were examined: two were characterized by information transfer efficiency; one was controlled by the proposed scheme.

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It has been reported that subsidiary behavior, including body movements, and irrelevant thoughts occur spontaneously during a vigilance situation. These activities are called task-irrelevant activity. To examine the effects of task attentiveness on task-irrelevant activity and on the subjective feeling of , 31 subjects were asked to engage in two types of signal detection tasks. The body movements were measured by recording the rotating angle of a swivel chair that the subject sat on. More task-irrelevant thoughts and subsidiary behavior occurred accompanied by higher subjective feeling of in the low attentive task than in the high attentive task. These findings indicate the possibility of the task-irrelevant activity as an index of subjective .

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As a consequence of a lack of balance between the levels of difficulty of a game and the players’ skills, the resulting experience for players might be frustrating (too difficult) or boring (too easy). Players having a bad experience could impact game creators negatively, leading to irreparable damage. The main motivation of this study was to find effective ways to reduce the gap between skills and difficulty,to help developers create a more suitable experience for players. This paper shows the results of applying Neural Networks and Support Vector Machines to data collected from the pressure exerted to a gamepad’s button with the purpose of finding patterns that can help predict: difficulty, fun, frustration,

,valence, arousal and dominance at a determined time. We obtained results with an accuracy of 83.64 % when predicting , around 70 % of accuracy classifying frustration, fun, difficulty and dominance.

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E-learning is the computer and network-enabled transfer of skills and knowledge. In e-learning systems, emotions are critical for learners to create positive contexts for optimal learning. In particular, increasing learner motivation by stimulating their interest is crucial. To data, however, few e-learning systems have derived emotions from eye tracking data. With eye tracking equipment, we recorded the eye movements of learners and calculated their eye metric indexes, which we focused on to explore their relationship to two learners' emotions groups: interest and groups. We designed and implemented a prototype and experimentally evaluated it.

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Understanding the other person completely results in since there will be no transfer of actual'information'thereafter between the two systems of consciousness.In order to avoid in human exchange, some techniques of communication are needed to generate ceaselessly new information which will give the sense of 'wonder'to receiver.'Difficulty of style'or abstruseness is one of this technique to keep the sense of edification through the unending process of interpretation.Seclusion of the source of information such as holy books or saints from the secular world is the other method.Disclosure of the information should be restrited to very special occasions so that the negentropy('mana')will not be exhausted.The praise for 'mutual understanding'and equality in the ideology of modern humanism, reducing differences and mysteriousness of the other, seems to add in various scenes of human communication.The logico-structural relationships between the diametrical sub-worlds on the 'Tetrahedron model of the symbolic universe'(presented by the author in Sociology of Laughter, Sekaisisosha, 1983)are discussed in terms of mutual misunderstaning and reification.

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It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, , sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.

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Self-paced e-learning provides much more freedom in time and locale than traditional education as well as diversity of learning contents and learning media and tools. However, its limitations must not be ignored. Lack of information on learners' states is a serious issue that can lead to severe problems, such as low learning efficiency, motivation loss, and even dropping out of e-learning. We have designed a novel e-learning support system that can visually observe learners' non-verbal behaviors and estimate their learning states and that can be easily integrated into practical e-learning environments. Three pairs of internal states closely related to learning performance, concentration-distraction, difficulty-ease, and interest-

, were selected as targets of recognition. In addition, we investigated the practical problem of estimating the learning states of a new learner whose characteristics are not known in advance. Experimental results show the potential of our system.

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In interactive systems, it is important to keep users' attention and not to get them bored. This paper explains our dialog corpus annotated with boredome information, and reports the analysis results.

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