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    Item type:Publication,
    Emotion-based music player
    (2019-07-01)
    Chankuptarat, Krittrin
    ;
    Sriwatanaworachai, Raphatsak
    ;
    Nowadays, people tend to increasingly have more stress because of the bad economy, high living expenses, etc. Listening to music is a key activity that assists to reduce stress. However, it may be unhelpful if the music does not suit the current emotion of the listener. Moreover, there is no music player which is able to select songs based on the user emotion. To solve this problem, this paper proposes an emotion-based music player, which is able to suggest songs based on the user's emotions; sad, happy, neutral and angry. The application receives either the user's heart rate or facial image from a smart band or mobile camera. It then uses the classification method to identify the user's emotion. This paper presents 2 kinds of the classification method; the heart rate-based and the facial image-based methods. Then, the application returns songs which have the same mood as the user's emotion. The experimental results show that the proposed approach is able to precisely classify the happy emotion because the heart rate range of this emotion is wide.
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    Item type:Publication,
    Examining the critical success factors of startup in Thailand using structural equation model
    (2018-11-13)
    Nalintippayawong, Srinual
    ;
    Waiyawatpattarakul, Nattakit
    ;
    Startup is a fast-growing business model by funding from investors, however, it also has a high failure rate and risk. This research aims to examine critical success factors of and their relations in Thai startups. Structural equation model is applied for studying causal relationships between factors by using factor analysis and multivariable regression analysis. Based on sixteen observed variables, the results show that there are four critical success factors of Thai startups, namely support partner, business model, market opportunity, and customer perspective. Especially, the factors of the business model and support partner have direct effects on potential and success in startups. This research is a knowledge framework which assists, not only young startups to succeed their business, but also investors to evaluate investments in startups. Moreover, the paper also provides a literature review which is useful for researchers in the area of a startup.
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    Item type:Publication,
    A system for research community annotation
    (2017-08-25)
    Community detection as an important task that allows understanding of complex networks has attracted much research attention. However, existing research stops at uncovering the community structures, from which the semantic meaning of individual communities cannot be inferred directly. This paper proposes to semantically annotate communities detected in a network. In particular, a system for annotating the research communities in a bibliographic network is developed. An unsupervised method is adopted to generate annotations according to three criteria, 1) the annotations should be semantically relevant with the community, 2) the annotations should be discriminative across communities, and 3) the annotations should have high topic coverage. The system shows that the generated annotations effectively enable the interpretation and understanding of large and various research communities, advancing existing research into community detection for community comprehension.