• Journal of IKEEE
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• v.24 no.2
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• pp.654-660
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• 2020

Through the output of brain waves during muscle operation, this paper checks whether it is possible to find characteristic vectors of brain waves that are capable of dividing left and right movements by extracting brain waves in specific areas of muscle signal output that include the motion of the left and right muscles or the will of the user within EEG signals, where uncertainties exist considerably. A typical surface EMG and noninvasive brain wave extraction method does not exist to distinguish whether the signal is a motion through the degree of ionization by internal neurotransmitter and the magnitude of electrical conductivity. In the case of joint and motor control through normal robot control systems or electrical signals, signals that can be controlled by the transmission and feedback control of specific signals can be identified. However, the human body lacks evidence to find the exact protocols between the brain and the muscles. Therefore, in this paper, efficiency is verified by utilizing the results of application of CSP (Common Spatial Pattern) filter to verify that the left-hand and right-hand signals can be extracted through brainwave analysis when the subject's behavior is performed. In addition, we propose ways to obtain data through experimental design for verification, to verify the change in results with or without filter application, and to increase the accuracy of the classification.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.31-38
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• 2016

The brain and muscles both of which are composed of top-down structure occur the connectivity with the change of Electroencephalogram(EEG) and Electromyogram(EMG). In this paper, we studied the difference of functional connectivity between brain and muscles that by applying coherence method to EEG and EMG signals when users exercised upper limb with and without the movement intention. The changes in the EEG and EMG signals were inspected using coherence method. During the upper limb exercise, the mu (8~14 Hz) and beta (15~30 Hz) rhythms of the EEG signal at the motor cortex area are activated. And then the beta and piper (30~60 Hz) rhythms of the EMG signal are activated as well. The result of coherence analysis between EEG and EMG showed the coefficient of active exercise including movement intention is significantly higher than passive exercise. The coherence relations between cognitive response and muscle movement could interpret that the connectivity between the brain and muscle appear during active exercise with movement intention. The feature of coherence between brain and muscles by the status of movement intention will be useful in designing the rehabilitation system requiring feedback depending on the users' movement intention status.

• Archives of design research
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• v.15 no.1
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• pp.59-67
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• 2002

In accordance with the fast changing circumstance, universities are now reaching, beyond the education place of simple delivery of knowledge and exchange of information, to a place of developing a specialty program related with the region and industry to achieve a competitive edge in education. Through these academic-industrial collaboration program, special knowledge and human resources in the university are utilized in the society and it may contribute to the development of industry and breed of career people based upon the real job site can be achieved. In addition, through the practical operation of such developed program, university may contribute to the enhancement of the competitiveness of the corporation to the activation and acceleration of the regional economy and finally to the enhancement of competitiveness of national industry in international level. This study tries to develop 3 technical instruction and support program related with the legion and industry which may conform to the ideals of university and its goal of education and can provide a platform for the education that is closely related with the regional industry and real job site iud may cope actively with the upcoming knowledge society and fast changing regional circumstances. This study will make research and analyze needs of design support from the industry in order to develop a academic-industrial cooperative design support program for the furniture industry which conforms to the regional characteristic and feature and develop and present contents of program in three area of development of furniture design technology, build-up of furniture design information system and establishment of order based education system. The proposed program is supposed to be operated practically and effectively and contribute to the development of new product, to enhancement of company image and finally to the maximization of corporate profit. Also this study is epected to be used as an important material for establishment of order-based education system which confirms to the job site needs that may be analysed from feedback of product results and for practical learning.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.125-137
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• 2011

Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• The Mathematical Education
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• v.63 no.2
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• pp.165-186
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• 2024

Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

• The Korean Journal of Archival Studies
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• no.23
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• pp.87-139
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• 2010

Unlike in the past, a new paradigm has been presented which the use of records is much more important than the preservation of those in the present. It will be necessary for users to signalizes the value of records and to make themselves easily accessible to records in order that records should be more effectively used. To meet the needs of the times, it is the very 'Contents' that starts to attract public attention. National Archives in England produces and provides contents utilizing multi-media by using digital technology on various sorts of archives which England has. In addition to England, Asian Historical Records center in Japan in Japan makes Archival Contents Service reflecting users' needs and continues to update the latest contents. What is more, National Archives of Korea has recently promoted the introduction of digital archive by the change of archival paradigm in records management, and it is giving an impetus to the development of contents in the digital archive. In fact, it is crucial to keep as many contents as possible and to give service to public, but it will not be possible to get positive response from public and to offer much higher level of archival information service until the quality of contents is highly improved. Accordingly, this manuscript analyzed the feature and type of contents which National Archives of Korea provides with cases of both TNA in England and Asian Historical Records center in Japan, each of which has different characteristics. Also, it dealt with several methods of the usage of contents in those organizations. Furthermore, this study explained what kind of contents and feedback are given to users. Moreover, it divided the components of contents of three institutions as mentioned into three by information provided and evaluated the quality of contents by establishing the details of contents. In addition, there were implications for archives with regard to reference for building contents.