• Journal of KIISE:Databases
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• v.36 no.6
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• pp.434-445
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• 2009

Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1240-1248
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• 2006

In this paper, we present a new method for user selection, sub-band allocation, and power allocation in order to maximize the system throughput under the constraint of transmit power in multiuser downlink orthogonal frequency division multiple access (OFDMA) systems with partial channel quality information (CQI). In previous schemes, each user in one cell transmits CQI of all sub-bands to the base station, which requires enormous feedback overhead. Therefore, we proposed an efficient power allocation and modulation and coding selection scheme in which each user transmits partial CQI and one additional information to reduce the amount of feedback. Simulation results show that we can greatly reduce the amount of feedback than full feedback system.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.572-580
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• 2020

Recently released AI speakers show a pattern of interacting with the user by mainly with voice and simultaneously displaying simple and formal visual feedback through status LED light. This is due to the limitations of the product characteristics of the speaker, which makes it difficult to interact variously, and even such visual feedback is not standardized for each product, and thus does not give a consistent user experience. By maximizing the visual elements that can be expressed through color and abstract movement to assist voice feedback, the product can provide the user with an extended experience that includes not only functional satisfaction but also emotional satisfaction. In this study, after analyzing the interaction methods of the existing AI speakers, we examined the theory of color communication in order to expand the visual feedback effect, and examined the meaning and expression technique of Color Field Painting, an art genre that maximizes the emotional experience by using only color. Through this, the AI speaker's visual communication function was expanded by designing a way to feedback communication status using LED light.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1832-1840
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• 1999

Since the existed Korean Web IR systems generally use boolean system, it is difficult to retrieve the information to be wanted at one time. Also, because of the feature that web documents have the frequent abbreviation and many links, the keyword extraction using the inverted document frequency extracts the improper keywords for adding ambiguous meaning problem. Therefore, users must repeat the modification of the queries until they get the proper information. In this paper, we design and implement the relevance feedback agent system for resolving the above problems. The relevance feedback agent system extracts the proper information in response to user's preferred keywords and stores these keywords in preference DB table. When users retrieve this information later, the relevance feedback agent system will search it adding relevant keywords to user's queries. As a result of this method, the system can reduce the number of modification of user's queries and improve the efficiency of the IR system.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.225-234
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• 2021

Due to pandemic situations, the development of home robots that can make the house an optimized space for various activities is active. This study aims to confirm the effectiveness of approach or avoidance behavior for feedback positioning on the user experience, depending on the context in which the robot performs the task. Based on two types of the task contexts(Reactive vs. Proactive) and three types of robot feedback positioning(No move vs. Avoidance vs. Approach), six different scenarios were designed for experimental study. Likeability, perceived intelligence, rapport, negative attitude and predictability of behavior are measured for each conditions. The result showed the main effects of perceived intelligence, rapport, predictability in the context of tasks, and of likability, perceived intelligence, rapport in robot feedback positioning. The interaction effects were shown in likeability and perceived intelligence. In conclusion, approach-avoidance experiences can also be applied to robot behaviors as well, and the negative effects of avoidance have been significantly confirmed.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.69-77
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• 2020

This paper proposes an effective method of giving users feedback on 3-dimensional drawing and measures its performance to ensure that feedback can help users enter the correct position in 3D. In the experiment of drawing a given line shape using a hand-held controller, the user is provided with three levels of visual, auditory, and haptic feedback for the position input error. As a result of analyzing the position input accuracy according to the type of feedback, all types of feedback are able to significantly reduce errors, and visual feedback and haptic feedback are more effective than auditory feedback.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.17-24
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• 2011

Collaborative filtering system is the clustering about user is built and then based on that clustering results will recommend the preferred item to the user. However, building user clustering is time consuming and also once the users evaluate and give feedback about the film then rebuilding the system is not simple. In this paper, genre pattern of movie recommendation systems is being used and in order to simplify and reduce time of rebuilding user clustering. A Frequent pattern networks is used and then extracts user preference genre patterns and through that extracted patterns user clustering will be built. Through built the clustering for all neighboring users to collaborative filtering is applied and then recommends movies to the user. When receiving user information feedback, traditional collaborative filtering is to rebuild the clustering for all neighbouring users to research and do the clustering. However by using frequent pattern Networks, through user clustering based on genre pattern, collaborative filtering is applied and when rebuilding user clustering inquiry limited by search time can be reduced. After receiving user information feedback through proposed user clustering based on genre pattern, the time that need to spent on re-establishing user clustering can be reduced and also enable the possibility of traditional collaborative filtering systems and recommendation of a similar performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.186-189
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• 1996

In most of the recent research literature, network performance is expressed in terms of network engineering measures such as delay or loss. These performance measures are important to network owners and operators, but it is believed that user preferences should be the primary consideration which drives the resource allocation scheme. A network is only as valuable as its users perceive it to be. Therefore, it is advocated that the users themselves determine relative traffic priorities. This paper describes the role of feedback in network resource allocation, which could be part of a user-oriented framework for network operation and control. Feedback mechanism can also be used to improve the two types of efficiency in the network; network efficiency and economic efficiency.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1823-1824
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• 2008

We propose a remote controlled robot manipulator using force feedback joystick. User can control easily 5 d.o.f robot manipulator in 3 demensional space using general joystick. A force sensor attached in developed gripper sends signal to main robot controller so as to know gripper grasp the object. The signal also sent to user through force feedback joystick. We designed a dexterous 5 d.o.f robot manipulator analysis the kinematics and inverse kinematics. The robot was simply developed using serial RC motor. As a main robot controller, we use 32bit MPU(AT91SAM7256) and micro C/OS. To show the validity of our developed robot, a several experiments were demonstrated.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.10-13
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• 2015

This paper proposed a novel user's information feedback algorithm for improving network energy harvesting rate. The proposed algorithm is focused on determining energy harvesting users comparing increasing ratio of the amount of harvesting energy versus emitted energy and network threshold ${\alpha}$, which is critical harvesting parameter. Using this method, we can increase the rate of network energy harvesting preventing emitted energy from wasting inefficiently. The result of experiment in this paper shows that user's information feedback algorithm makes network energy harvesting rate more efficiently when it uses threshold ${\alpha}=15%$ to determine energy harvesting users.