• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.113-119
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• 2010

Wireless ad hoc network composed of low power devices has been operated in ISM bands. However, with the growing proliferation of wireless services, these bands are increasingly getting congested. In order to relieve the spectrum scarcity and inefficient spectrum utilization, ad ho cognitive radio was proposed. In this paper we propose the efficient spectrum sensing method to reduce power consumption and detect white space in ad hoc cognitive radio system. The wireless channel between a licensed user and CR systems is modeled as Gaussian channel, the distance between a licensed user and CR systems is assumed differently. Also, the wireless channel among CR systems is assumed as the perfect channel and the distance among CR systems is assumed close distance. CR systems sense the spectrum of the licensed user by using a energy detection method. From the simulation results, spectrum sensing performance of combining sensing result of CR systems with high received energy shows higher than combining sensing result of all CR systems and we can refer to the proposed sensing method in order to perform effective spectrum sensing with low power consumption.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.373-384
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• 2014

Data mining is to clarify pattern or correlation of mass data of complicated structure and to predict the diverse outcomes. This technique is used in the fields of finance, telecommunication, circulation, medicine and so on. In this paper, we selected risk factors of respiratory diseases in the field of medicine. The data we used was divided into respiratory diseases group and health group from the Gyeongsangbuk-do database of Community Health Survey conducted in 2012. In order to select major risk factors, we applied data mining techniques such as neural network, logistic regression, Bayesian network, C5.0 and CART. We divided total data into training and testing data, and applied model which was designed by training data to testing data. By the comparison of prediction accuracy, CART was identified as best model. Depression, smoking and stress were proved as the major risk factors of respiratory disease.

• Korean Journal of Cognitive Science
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• v.19 no.2
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• pp.107-123
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• 2008

The existing studies of a dialogue system can be classified into two major parts. One is a study for a practical system, and the other is a study to understand a principal of dialogue phenomena. The former focuses on robustness in real environment for dialogue systems. However, it cannot guarantee its performance in complicated dialogue environment. The latter has studied as the plan-based model typically. It has strong points that it can reflect complex dialogue phenomena and can infer user's intention in various situations. However, an initial design of this model is so complicated, and it is difficult for this model to be extended to the interaction model for response generation in a practical dialogue system. This paper proposes a new dialogue modeling using plan recognition and a discourse stark to effectively generate response in a practical dialogue system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9A
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• pp.719-726
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• 2009

CR systems performs spectrum sensing operation to detect the appearance of primary users. However, since it is not feasible to do spectrum sensing and data transmission simultaneously, they typically operate alternatively in a time domain. There have been an effort(8) to investigate the optimal spectrum sensing duration for maximum throughput for the scheme with cooperative spectrum sensing. This is based on an assumption that the communication channels between each secondary user and the fusion center are ideal and does not consider the effects of transmission error. Motivated by this, we here model the channels as binary symmetric channels and examined its effect on the maximum throughput and the associated optimal sensing duration. Analysis shows that the performance degradation due to the transmission error is smaller for the case of using the AND fusion rule than for the OR fusion rule.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.325-338
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• 2012

In this paper, a radio resource allocation scheme for a multi-hop relay transmission in cognitive radio (CR) system is proposed to support the employment of relay nodes in IEEE 802.22 standard for wireless regional area network (WRAN). An optimization problem is formulated to maximize the number of serving secondary users (SUs) under system constraints such as time-divided frame structure for multiplexing and a single resource-unit to every relay-hop. However, due to mathematical complexity, the optimization problem is solved with a sub-optimal manner instead, which takes three steps in the order of user selection, relay/path selection, and frequency selection. In the numerical analysis, this proposed solution is evaluated in terms of service rate denoting as the ratio of the number of serving SUs to the number of service-requesting SUs. Simulation results show the condition of adopting multi-hop relay and the optimum number of relaying hops by comparing with the performance of 1-hop system.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1036-1056
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• 2017

The rapid increase of ageing population and chronic disease patients cause high medical expenses, and it led an increased attention to digital healthcare. Smart car technologies for healthcare have been developing to recognize drivers' status and predict diverse driving environments. The present study aimed to understand the research trends of autonomous vehicle technologies of Korea and the United States through time series analysis, network analysis, visualization, and comparison between the two countries. The results suggest that cooperative study needs to be done in common research areas such as driver's safety and algorithms. It is also needed to conduct studies and benchmark about liking technique related to part-to-part and vehicle-to-vehicle as America's competitive advantaged area. In the US, diverse approaches of autonomous vehicle technologies have used to consider the characteristics of various age groups and passengers' health status through sensor, while in Korea, only one aspect, older drivers, is mentioned. Implications for the development direction of autonomous vehicle technologies with competitiveness in considering public health, ethics, and driver's safety and convenience are discussed in detail.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.211-218
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• 2008

In this paper, we proposed a new image summarization algorithm designed for automatically summarizing user's snapshot photos taken in a virtual environment based on user's context information and educational contents, and then presenting a summarized photos shortly after user's virtual reality experience. While other image summarization algorithms used date, location, and keyword to effectively summarize a large amount of photos, this algorithm is intended to improve users' memory retention by recalling their interests and important educational contents. This paper first describes some criteria of extracting the meaningful images to improve learning effects and the identification rate calculations, followed by the system architecture that integrates the virtual environment and the viewer interface. It will also discuss a user study to model the algorithm's optimal identification rate and then future research directions.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.395-404
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• 2021

Emoticons used in personal messengers have already become a one of industry. In this study, we want to explore what motivations people use emoticons and how they affect to purchasing behavior. We first looked into which emoticon usage motivation influenced the attitude of emoticon purchase, and then analyzed the research model through PLS-based structural equation modeling. The result found that fashion and fun/habit factors significantly explain attitudes to emoticon purchase, and attitude, subjective norms, and perceived self-control affect to purchase intention and purchase intention predict purchase behavior. This study showed the factors affecting the purchase of emoticons through a validated model, and the results suggest what motivation factors should be included in the marketing phase and advertising.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.469-476
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• 2022

As the 3D modeling technology and conversational algorithm is developed, digital humans are being used in various fields, and also virtual bankers have begun to appear in banks, including major banks such as Shin-Han Bank and Nong-Hyup Bank. However, most of the research of digital human mainly focus on its appearance, and research on robot persona that should be considered in anthropomorphizing a robot is insufficient. In this study, an experiment was conducted to find out the user experience of three scenarios (student ID receipt, deposit and withdrawal account opening, leasehold loan consultation) in which the level of anthropomorphism of the speech strategy and the level of personal information use differed in the specific context of banking. As a result of the study, social presence and usefulness had an interactive effect on the scenario and the level of anthropomorphism. There was no interaction effect on intimacy, trustworthiness, and perceived intelligence, but a tendency could be confirmed.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.808-811
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• 2022

Display under strong ambient lighting is perceived darker than it really is. Existing techniques for solving the problem in terms of software show limitations in that image enhancement techniques are applied regardless of ambient lighting or chrominance is not improved compared to luminance. Therefore, this paper proposes a visibility enhancement algorithm using deep learning to adaptively respond to ambient lighting values and an equation to restore optimal chrominance for luminance. The algorithm receives an ambient lighting value with the input image, and then applies a deep learning model and chrominance restoration equation to generate an image to minimize the difference between the degradation modeling of enhanced image and the input image. Qualitative evaluation proves that the algorithm shows excellent performance in improving visibility under strong ambient lighting through comparison of images applied with degradation modeling.