• Journal of the Ergonomics Society of Korea
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• v.28 no.1
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• pp.1-7
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• 2009

As products are getting more diverse and new products are entering the market faster, customers have trouble learning how to use them. User-oriented menu structures may solve this problem. In order to design user-oriented menu structures, spreading activation theory has been studied. The spreading activation test shows that the strong associative relationship between words has shorter response times. Based on the spreading activation test, asymmetric spreading activation was introduced and a hypothesis that in a well-designed menu structure, association between upper-low menu pairs is not affected by an activation direction was tested for this study. In this study the menu of a cellular phone (Model: SPH-w2900) was extracted, and underwent 1st spreading activation tests. Then, on each menu pair, response time differences (asymmetric transition) by accuracy and directions were analyzed to find out problems in labels and improve menu structures and vocabulary. Second spreading activation tests were conducted to check whether asymmetric transitions decreased. The results showed that response time differences (asymmetric transition) for activation directions were found to be dropped significantly. Asymmetric transitions in spreading activation presented in this study will be helpful to define user-oriented menu structures.

• ETRI Journal
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• v.38 no.5
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• pp.885-895
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• 2016

The lowest power mode (passive-standby mode) was proposed for reducing the power consumption of set-top boxes in a standby state when not receiving content. However, low-power set-top boxes equipped with the lowest power mode have been rarely commercialized because of their low-quality user experience. In the lowest power mode, they deactivates almost all of operational modules and processes, and thus require dozens of seconds for activation latency (that is, the latency for activating all modules of the set-top boxes in a standby state). They are not even updated in a standby state because they deactivate their network interfaces in a standby state. This paper proposes an adaptive standby mode scheduling method for improving the user experience of such boxes. Set-top boxes using the proposed method can analyze the activation pattern and find the frequently used time period (that is, when the set-top boxes are frequently activated). They prepare for their activation during this frequently used time period, thereby reducing the activation latency and enabling their update in a standby state.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.167-176
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• 2013

User-created text data are increasing rapidly caused by development of social media. In opinion mining, User's opinions are extracted by analyzing user's text. A primary goal of sentiment analysis as a branch of opinion mining is to extract user's opinions from a text that is required to build a list of emotion terms. In this paper, we built a list of emotion terms to analyse a sentiment of social media using Facebook as a representative social media. We collected data from Facebook and selected a emotion terms, and measured the dimensions of valence and activation through a survey. As a result, we built a list of 267 emotion terms including the dimension of valence and activation.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.143-148
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• 2022

In this paper, we employ deep neural network (DNN) to discern Android user interaction data distribution from artificial data distribution. We utilize real Android user interaction trace dataset collected from [1] to evaluate our DNN design. In particular, we use sequential model with 4 dense hidden layers and 1 dense output layer in TensorFlow and Keras. We also deploy sigmoid activation function for a dense output layer with 1 neuron and ReLU activation function for each dense hidden layer with 32 neurons. Our evaluation shows that our DNN design fulfills high test accuracy of at least 0.9955 and low test loss of at most 0.0116 in all cases of artificial data distributions.

• Journal of the Korean Society for information Management
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• v.37 no.4
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• pp.27-60
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• 2020

Sejong City Library information services and programs proposed in this study are proposed by combining cases of local representative libraries and overseas libraries. As a feature of the proposal, first, various information services that can be provided by the Sejong City Library are proposed by area, by user, by data type, by media, by partner institution, etc. Second, by reinforcing user programs for each life cycle, various reading programs by age and interest, such as reading discussion, reading experience, and reading events, are provided. Reinforce user-based programs that reflect the characteristics of Sejong City's population, such as adult, child, and family programs. Third, secure and utilize maker space space. Fourth, the reading program developed by the Sejong City Library is promoted and shared in cooperation with local libraries. Fifth, induce participation of local residents in Sejong City, volunteer activities and talent donation. Sixth, propose library information services using library websites and social media, and develop channels for mutual cooperation with users.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.1-146
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• 2001

The researches of science and engineering need the latest information from internet resources. But searching and filtering processes of appropriate web documents from huge internet resources are very complex as well as having some repeated procedures. In this paper, I propose a Personalized Agent System(PAS), which can filter World Wide Web Documents that the user is interested, such as papers. To do this, PAS uses a modified spreading activation neural network which 1 propose here. PAS observes the user´s local paper database to analyze, adapt and learn the user interests, and the then constructs the user-specified neural network model by the analyzed interests ...

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.135-142
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• 2007

Icon conveys symbolic information which they have become ubiquitous as main element of GUI. However, users often cannot intuitively understand its functional meanings. Icon has to be designed for users to easily understand functional meanings. In order to evaluate icon, the spreading activation model can be used to effectively understand the process of information retrieval. In asymmetric spreading activation model is that in the two nodes the degree of spreading activation is different according to direction. Thus, asymmetric spreading activation theory was performed evaluating the strength of association when users see visual image to associate their verbal meaning (visual image - verbal meaning pair) and users see verbal meaning to associate their visual image (verbal meaning - visual image pair). According to the direction, this study hypothesizes that the well-designed icons have symmetric relationship rather than asymmetric relationship between the two pairs. The strength of association is measured through the reaction time and the accuracy rate. In performing SAT (spreading activation test), the ten icons were selected as word processing software icons. After first SAT, newly designed icons were developed based on Korean mental model, and second SAT was conducted using them. The results showed that the accuracy rate of newly designed icon has been improved. Also there is significant difference of reaction time between current icons and newly designed icons. Well-designed icon is confirmed that the strength of association relationship arises symmetrically rather than asymmetrically between the two pairs. User centered icons could be designed by improving the strength of association between the two pairs. Asymmetric SAT evaluates the strength of the association between the visual image and the verbal meanings to contribute to the development of icon which it related to human's association structure.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1111-1119
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• 2003

The research of science and engineering needs the latest information from internet resources. But it is a complex and repeated procedure to search and filter web documents from the huge Internet resources. In this paper, we propose the PREA system, which can organize the research paper databases and search World Wide Web documents that the user is interested in. It observes the usage of the local Paper databases and presented web documents and then constructs a profile intelligently. However, to make a profile, we used the modified spreading activation network(MSAN) so that the PREA can search and filter web documents by semantic meaning of user's interest in realtime. The system constructed in multi-agents manner that can cooperate together effectively. The results show the effectiveness of our system to search web documents compared with a commercial search engine.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.11
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• pp.911-918
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• 2014

In this paper, a selective activation strategy of cohesive elements using user subroutine UMPC was studied as an efficient solution for the added compliance problem in cohesive zone model crack propagation analyses. The cohesive elements were inserted between every bulk elements in region where cracks were expected to initiate and propagate, but initially not activated by tying the cohesive nodes using multi-point constraints. During analyses, the cohesive elements for which specified criterion was met were selectively activated by releasing the constraints. The effect of initial cohesive stiffness and the release criterion on the crack propagation behavior was carefully investigated.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.203-212
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• 2024

Simultaneous motion is essential in the activities of daily living (ADL). For motion intention recognition, surface electromyogram (sEMG) and corresponding motion label is necessary. However, this process is time-consuming and it may increase the burden of the user. Therefore, we propose a simultaneous motion recognition framework using data augmentation based on muscle activation model. The model consists of multiple point sources to be optimized while the number of point sources and their initial parameters are automatically determined. From the experimental results, it is shown that the framework has generated the data which are similar to the real one. This aspect is quantified with the following two metrics: structural similarity index measure (SSIM) and mean squared error (MSE). Furthermore, with k-nearest neighbor (k-NN) or support vector machine (SVM), the classification accuracy is also enhanced with the proposed framework. From these results, it can be concluded that the generalization property of the training data is enhanced and the classification accuracy is increased accordingly. We expect that this framework reduces the burden of the user from the excessive and time-consuming data acquisition.