• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.259-268
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• 2018

The purpose of this study is to propose a training method customized to the level of cognitive abilities to increase users' interest and engagement while using cognitive function training contents. The level of cognitive ability of the users was based on the clustering based on the users' information and Mini-Mental Statue Examination-Korea Child test score using the K-means algorithm applied collaborative filtering. The results were applied to the integrated cognitive function training system, and the contents order and difficulty level of the cognitive function training area were recommended to the user's cognitive ability level. Particularly, the contents difficulty control was designed to give a high immersion feeling by applying the 'flow theory' method that users can repeatedly feel tension and comfort. In conclusion, the user-customized cognitive function training method proposed in this paper can be expected to be more effective and rehabilitative results than existing therapists' subjective setting of contents order and difficulty level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2849-2865
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• 2012

In order to block mobile junk messages automatically, many studies on spam filters have applied machine learning algorithms. Most previous research focused only on the accuracy rate of spam filters from the view point of the algorithm used, not on individual user's preferences. In terms of individual taste, the spam filters implemented on a mobile device have the advantage over spam filters on a network node, because it deals with only incoming messages on the users' phone and generates no additional traffic during the filtering process. However, a spam filter on a mobile phone has to consider the consumption of resources, because energy, memory and computing ability are limited. Moreover, as time passes an increasing number of feature words are likely to exhaust mobile resources. In this paper we propose a spam filter model distributed between a users' computer and smart phone. We expect the model to follow personal decision boundaries and use the uniform resources of smart phones. An authorized user's computer takes on the more complex and time consuming jobs, such as feature selection and training, while the smart phone performs only the minimum amount of work for filtering and utilizes the results of the information calculated on the desktop. Our experiments show that the accuracy of our method is more than 95% with Na$\ddot{i}$ve Bayes and Support Vector Machine, and our model that uses uniform memory does not affect other applications that run on the smart phone.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.487-497
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• 2003

There have been many filtering systems covering mail or news. Documents filtered by them consist of general text or HTML. XML is emerging as a new standard for information exchange. So, filtering systems need new approaches in dealing with XML documents. Our system suggests a method to describe user profiles with XML's ability to represent schema and structure. An user profile is made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. More, it is different from the existing systems in extracting part of a document. An user profile is reflected in XML query to get part of an XML document.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.126-130
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion (FBFE) based on virus evolutionary genetic algorithm(VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter (EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FBFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by identifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.59-67
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• 1998

A quick and automatic detection with no harm to the goods is very important task for improving quality control, process control and labour reduction. In real fields of industry, defect detection is mostly accomplished by skillful workers. A narrow band eliminating spatial filter having characteristics of removing the specified spatial frequency is developed by the author, and it is proved that the filter has an excellent ability for on-line and real time detection of surface defect. By the way,. this spatial filter shows a ripple phenominum in filtering characteristics. So, it is necessary to remove the ripple component for the improvement of filter gain, moreover efficiency of defect detection. The spatial filtering method has a remarkable feature which means that it is able to set up weighting function for its own sake, and which can to obtain the best signal relating to the purpose of the measurement. Hence, having an eye on such feature, theoretical analysis is carried out at first for optimal design of narrow band eliminating spatial filter, and secondly, on the basis of above results spatial filter is manufactured, and finally advanced effectiveness of spatial filter is evaluated experimentally.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.387-392
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• 2007

In this study performance evaluation of filtering system were made on the clean air supply system to show it's ability to eliminate the air contaminants. The evaluation was conducted inside the 3,200CMH scale wind tunnel and under the same environment that is effected by yellow dust and similar particle and gas phase contaminants in semi-conductor and FPDs industries. (1) The result of experimental for particle contaminants, the particle removing efficiency was 40% on condition that the air velocity is 2.5m/s, L/G ratio : 0.05, electrified voltage : (+)5.8kV with electric charger and (-)3.5kV with eliminator. (2) The gas phase removing efficiency for $NH_3$ : 80%, $SO_X$ : 70% and $NO_X$ : 40% on condition that the air velocity is 2.5m/s, L/G ratio : 0.05.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.11-17
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• 2010

In this paper, we propose a recommendation system for supporting self-directed programming language education. The system is a recommendation system using collaborative filtering based on learners' level and stage. In this study, we design a recommendation system which uses collaborative filtering based on learners' profile of their level and correlation profile between learning topics in order to increase self-directed learning effects when students plan their learning process in e-learning environment. This system provides a way for solving a difficult problem, that is providing programming problems based on problem solving ability, in the programming language education system. As a result, it will contribute to improve the quality of education by providing appropriate programming problems in learner"s level and e-learning environment based on teaching and learning method to encourage self-directed learning.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.51-58
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• 2010

Programming education needs learning which is adjusted individual learners' level of their learning abilities. Recommendation system is one way of implementing personalized service. In this research, we propose recommendation method which learning items are recommended for individual learners' learning in web-based programming education environment by. Our proposed system for leveled programming education provides appropriate programming problems for a certain learner in his learning level and learning scope employing collaborative filtering method using learners' profile of their level and correlation profile between learning topics. As a result, it resolves a problem that providing appropriate programming problems in learner's level, and we get a result that improving leaner's programming ability. Furthermore, when we compared our proposed method and original collaborative filtering method, our proposed method provides the ways to solve the scalability which is one of the limitations in recommendation systems by improving recommendation performance and reducing analysis time.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.661-670
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• 2006

With the development of e-Commerce and the proliferation of easily accessible information, information filtering systems such as recommender and SDI systems have become popular to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. Until now, many information filtering methods have been proposed to support filtering systems. XML is emerging as a new standard for information. Recently, filtering systems need new approaches in dealing with XML documents. So, in this paper our system suggests a method to create multiform user profiles with XML's ability to represent structure. This system consists of two parts; one is an administrator profile definition part that an administrator defines to analyze users purchase pattern before a transaction such as purchase happens directly. an other is a user profile creation part module which is applied by the defined profile. Administrator profiles are made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. Proposed system builds user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.619-622
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• 2004

For recent years, hacking is in the trends of making excessive traffic unnecessarily to obstruct the service by getting a system's performance down. And we can also see systems paralyzed in service ability due to the flash crowds of normal traffic to a popular website. This is an important problem certainly solved in the point of QoS guarantee for the clients. It is known that the former is DDoS(Distributed Denial of Service) attack and the latter is FE(Flash Event). These two are samely anomalous traffic because these make excessive congestion on the network or system and downgrade the system's service ability. In this paper, we propose a scheme for protecting the system against anomalous traffic and for guaranteeing the QoS. For this, a server records and maintains the information of clients accessed more than one time before when it is in normal condition. When it falls into the congestion, the records are used for filtering the spoofed IP. We send and receive the ICMP request/reply packet to know whether the IP is spoofed. And we also propose for applying the object spliting of CDN to guarantee the QoS in the initial FE situation.