• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.1-8
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• 2020

In recent years, due to the exponential increase in internet data, many fields such as deep learning have developed, but side effects generated as commercial advertisements, such as viral marketing, have been discovered. This not only damages the essence of the internet for sharing high-quality information, but also causes problems that increase users' search times to acquire high-quality information. In this study, we define advertisement as "a text that obscures the essence of information transmission" and we propose a model for filtering information according to that definition. The proposed model consists of advertisement filtering and advertisement filtering performance improvement and is designed to continuously improve performance. We collected data for filtering advertisements and learned document classification using KorBERT. Experiments were conducted to verify the performance of this model. For data combining five topics, accuracy and precision were 89.2% and 84.3%, respectively. High performance was confirmed, even if atypical characteristics of advertisements are considered. This approach is expected to reduce wasted time and fatigue in searching for information, because our model effectively delivers high-quality information to users through a process of determining and filtering advertisement paragraphs.

• Korean Journal of Cognitive Science
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• v.24 no.3
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• pp.271-300
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• 2013

Human and animals are born with an intuitive ability to determine approximate numerosity. This ability is termed approximate number sense (hereafter, number sense). Evolutionarily, number sense is thought to be an essential ability for hunting, gathering and survival. According to previous research, children with mathematical learning disability have impaired number sense. On the other hand, individuals with more accurate number sense have higher mathematical achievement. These results support the hypothesis that number sense provides a basis for the development of mathematical cognition. Recently, researchers have been examining whether number sense training can lead to enhancement in mathematical achievement and changes in brain activity in relation to mathematical problem solving. Numerosity which basically represents discontinuous quantity is expected to be closely related to continuous quantity such as representations of space and time. A theory of magnitude (ATOM) states that processing of number, space and time is based on a common magnitude system in the posterior parietal cortex, especially the intraparietal sulcus. The present paper introduces current literature and future directions for the study of the common magnitude system.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.285-296
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• 2004

The rapid progress of IT technologies promoted the foundation to offer users 'Any Time, Any Where, Any Service', and wireless internet services made it possible to use wired internet services while traveling. The previous academic administration management system having migrated from wired to wireless was dependent on mobile equipments' platform because of not being constructed on standard surroundings. And in the aspect of faculty system, course coordinator plays an significant role in building curricula and manage them, and finally counseling students with regard to them. But the course coordinator can't afford to advise students on which fields of their faculty fit them and which courses they have to take. We propose a mobile course coordinator system to help students learn profound courses of their major fields. Also the proposed system is implemented by using JAVA and WIPI technology, so that it is platform-independent. A mobile course coordinator system has an inference engine considering not only course trees which tell informations about the courses in every fields, but also personal courses that students have taken. The inference engine calculates three weights, representing the significance of each course considering every fields, the score of prerequisite courses which a student have taken, and the suitability in which department each student fits. When students apply for taking lectures, a mobile course coordinator system recommends them the most suitable courses. A mobile course coordinator system is able to substitute for the course coordinator who is counseling students. And the students with personal cellular phone are able to keep tracking their courses, and improve their knowledge about major with taking courses which the system's inference engine will advice.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.421-434
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• 2008

As computer graphics, virtual reality and augmented reality technologies have been developed, in many application areas based on those techniques, interaction for 3D space is required such as selection and manipulation of an 3D object. In this paper, we propose a framework for a vision-based 3D interaction which enables to simulate functions of an expensive 3D mouse for a desktop environment. The proposed framework includes a specially manufactured interaction device using three-color LEDs. By recognizing position and color of the LED from video sequences, various events of the mouse and 6 DOF interactions are supported. Since the proposed device is more intuitive and easier than an existing 3D mouse which is expensive and requires skilled manipulation, it can be used without additional learning or training. In this paper, we explain methods for making a pointing device using three-color LEDs which is one of the components of the proposed framework, calculating 3D position and orientation of the pointer and analyzing color of the LED from video sequences. We verify accuracy and usefulness of the proposed device by showing a measurement result of an error of the 3D position and orientation.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• Journal of Music and Human Behavior
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• v.14 no.1
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• pp.85-108
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• 2017

The purpose of this study was to examine how a therapeutic drumming intervention would impact middle school students with regard to school violence prevention. Participants were all in the third-year class of a middle school in Korea. A school music teacher and a music therapist designed and implemented the program collaboratively, and mainly used dyadic, synchronized, and improvisational drumming based on the Social Emotional Learning core competencies. A total of 65 students participated in a weekly 45-minute program for 10 weeks. Ten participants out of 65 were selected for interviews and the rest of the 55 participants were asked to fill out an open-ended survey. Content analysis of the survey and interviews produced 492 meaningful statements, which were categorized into seven themes: somatic responses to drumming, emotional processing, group cohesion, empathy, relationship with peers, self-esteem, and self-regulation. The findings indicated that dyadic, synchronized, and improvisational drumming may promote prosocial behaviors in students of this age. The author discussed that drumming produces physical input directly from the instruments, which prompts students to identify and empathize with their own or others' emotions. This study therefore suggests that collaborative work between school music teachers and music therapists may positively impact middle school students' prosocial behaviors, as they pertain to school violence in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.699-707
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• 2020

With the development of deep learning technology, voice processing-related technology is applied to various areas, such as STT (Speech To Text), TTS (Text To Speech), ChatBOT, and intelligent personal assistant. In particular, the STT is a voice-based, relevant service that changes human languages to text, so it can be applied to various IT related services. Recently, many places, such as general private enterprises and public institutions, are attempting to introduce the relevant technology. On the other hand, in contrast to the general IT solution that can be evaluated quantitatively, the standard and methods of evaluating the accuracy of the STT engine are ambiguous, and they do not consider the characteristics of the Korean language. Therefore, it is difficult to apply the quantitative evaluation standard. This study aims to provide a guide to an evaluation of the STT engine conversion performance based on the characteristics of the Korean language, so that engine manufacturers can perform the STT conversion based on the characteristics of the Korean language, while the market could perform a more accurate evaluation. In the experiment, a 35% more accurate evaluation could be performed compared to the existing methods.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.234-243
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• 2008

The aim of this study was to provide the way of activation plans of leisure activities for older people through the current status and problems in welfare center for the elderly in Korea. Various social phenomena and issues have been found to occur in rapidly social-structure changes and urban civilization. Especially, processing an aging society for no preparation is one of the broader question of our country. Developing the scientific and civilization lengthening our span of life is given more leisure time than past. Unfortunately, older people could not independently stand for in their leisure, if society does not support for them. It means that they might feel the enough time to monotone life, depression and a sense of alienation. The following ideas would be expressed to the way of activation plans of elderly leisure. First, the elderly leisure facilities for leisure and publicity activities should be supplemented or strengthened. Second simple entertainment-oriented programs in the physical and psychology learning to adapt for them should be obtained through leisure activities for older people. Third, more senior recreation specialists or therapists should be educated for leisure activities. Fourth, the concept of leisure in older people's idea should be changed through the education. Fifth, people who work in the welfare center for the elderly should develop the leisure programs or activities for older people. Last the new culture of leisure concept should be constructed in our society between the two and three generation for sharing and participating the leisure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.409-416
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• 2020

Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.315-324
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• 2011

In Web environment, a flood of spam causes serious social problems such as personal information leak, monetary loss from fishing and distribution of harmful contents. Moreover, types and techniques of spam distribution which must be controlled are varying as days go by. The learning based spam classification method using Bag-of-Words model is the most widely used method until now. However, this method is vulnerable to anti-spam avoidance techniques, which recent spams commonly have, because it classifies spam documents utilizing only keyword occurrence information from classification model training process. In this paper, we propose a spam document detection method using a characteristic of repeating words occurring in spam documents as a solution of anti-spam avoidance techniques. Recently, most spam documents have a trend of repeating key phrases that are designed to spread, and this trend can be used as a measure in classifying spam documents. In this paper, we define six variables, which represent a characteristic of word repetition, and use those variables as a feature set for constructing a classification model. The effectiveness of proposed method is evaluated by an experiment with blog posts and E-mail data. The result of experiment shows that the proposed method outperforms other approaches.