• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.3
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• pp.309-316
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• 2010

In this study, a digital particle holographic system and its application to channel-flow measurements were investigated. A double-exposure hologram recording system that is capable of recording digital holograms in a short time interval was developed. A correlation coefficient method was used to determine the focal plane of particles. The Wiener filter was used to remove noises and improve image quality. Two-threshold and image segmentation methods were used for binary image transformation. The cross-correlation method was used for particle pairing. The developed system was employed to study channel flow fields, and the axial velocities of channel flow were measured. The measurement errors are acceptable, and this proves the feasibility of using the digital particle holographic system as a good tool for flow-field measurements.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.19-28
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• 2017

Various methods for reducing the load on the server have been implemented in performing face recognition remotely by the spread of IP security cameras. In this paper, IP surveillance cameras at remote sites are input through a DSP board equipped with face detection function, and then face detection is performed. Then, the facial region image is transmitted to the server, and the face recognition processing is performed through face recognition distributed processing. As a result, the overall server system load and significantly reduce processing and real-time face recognition has the advantage that you can perform while linked up to 256 cameras. The technology that can accomplish this is to perform 64-channel face recognition per server using distributed processing server technology and to process face search results through 250 camera channels when operating four distributed processing servers there was.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.255-260
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• 2020

In this paper, I propose an efficient brand identity strategy by topic modeling the Instagram posts, one of SNS(Social Network Service) having more than 1billion world-wide and 500 million daily users. Since the 92% age groups of the Instagram is 18~50 years old (59% 18~29y and 33% 30~49), I set research analysis target three mobile commerce sites to dress and cosmetics sales sites that sale apparels cosmetics and gadgets that recently opened and have operated marketing on diverse channel including SNS. By topic modeling SNS posts for 6 months after launching the site that tagged each m-commerce site brand name or company name, I validate companies' brand identity strategy works effectively and suggest moderation of strategy for brand image. As a result, I found one of three mobile commerce site has different brand image by users and need different identity set up.

• Archives of design research
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• v.18 no.4 s.62
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• pp.205-214
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• 2005

The purpose of this study is to find an efficient marketing strategy in terms of media channel communications using one specific case study. Results of previous studies have shown that consumers' exposure to TV, newspaper, radio and magazine related to description of corporate image tends to be influential for consumers' product image, which mainly consists of product preference, expertise, and credibility. It means that media strategy should be different, depending on what kinds of image they try to be purposive. In conclusion, we concluded that TV and radio should be the best vehicle for increasing consumers' positive preference rather than those of newspaper and magazine. Newspaper and magazine are also influential in terms of expertise, and newspaper and magazine should be better than TV and radio in terms of credibility. The results of this study should be similar to previous studies in that TV and radio should be more inducing interest, and print media should be more credible than TV and radio.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2141-2145
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• 2015

A new broadcasting signal transmission, which can save its channel bandwidth using compressive sensing(CS), is proposed in this paper. A new compression technique, which uses two dimensional discrete wavelet transform technique, is proposed to get high sparsity of multimedia image. A L1 minimization technique based on orthogonal matching pursuit is also introduced in order to reconstruct the compressed multimedia image. The CS enables us to save the channel bandwidth of wired and wireless broadcasting signal because various transmitted data are compressed using it. A $256{\times}256$ gray-scale image with compression rato of 20 %, which is sampled by 10 Gs/s, was transmitted to an optical receiver through 20-km optical transmission and then was reconstructed successfully using L1 minimization (bit error rate of $10^{-12}$ at the received optical power of -12.2 dB).

• The Journal of Bigdata
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• v.2 no.1
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• pp.27-39
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• 2017

The importance of online communication is getting increased by the rapid growth of smartphone supply and Social Network Service (SNS) use. Catching up with the trend, firms are actively use SNS to improve brand image, promote products, and communicate with customer. On the one hand, SNS is the channel for firms' marketing activities, but on the other, it is also the channel where the events related to the firms propagate in real time. Firms are led to unexpected state of crisis, when events are quickly spread out on SNS. Then firms are assessed their image by the way they deal with the state of crisis. This paper proposes to figure out user response on SNS according to each crisis response strategies by analyzing event-related twitter data when crisis situations of firms arise. We classify crisis response strategies into response attitude, defensive and accommodative response, and response speed, fast and slow response. This paper suggests optimal crisis response strategy to firms regarding state of crisis propagated on SNS.

• Korean Business Review
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• v.7
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• pp.57-77
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• 1994

우리에게 미국시장은 매우 중요하다. 따라서 최근에 미국시장에서 일어나고 있는 한국과의 통상마찰은 우리가 적극적이고 슬기롭게 대처해 나가야 할 부분이다. 이러한 문제에 대한 대안으로 통상로비 전략의 구축은 중요한 통상마찰의 해소 방안이 될 수 있다. 지금까지 논의한 통상로비에 관한 이론과 외국의 대미(對美)로비 실태파악과 우리의 로비전략을 살펴보았다. 여기에서는 앞에서 언급한 한국의 대(對)미 통상로비전략을 간단하게 요약하여 정리해 봄으로써 연구 결론을 내리고자한다. 즉, 통상로비전략을 네 가지 차원으로 나누어 설명하면 다음과 같다. 첫째 기본전략으로써 미국에 관한 철저연구와 우리주장의 논리적 타당성을 얻기 위해서 문화홍보에 역점을 두어야 하고 대중 동원형(Grass Roots)로비를 효율적으로 전개할 필요성이 있다. 둘째, 정부의 대응전략으로 미국내 한국에 대한 여론조사를 실시하여 한국의 이미지와 그러한 인식이 생성된 배경의 파악이 중요하다. 한국 내에서의 대미(對美)로비를 중시하여 한국에 파견된 미국대사관 직원, 해외방송, 신문, 특파원에 대한 한국 홍보강화와 해외 홍보기금조성을 통하여 정부차원에서 해외홍보를 적극 권장하고, 정부부처간이나 기업 간에 연락 및 협력을 강화한다든지 민간기업의 로비를 간접지원 하는데 노력해야 할 것이다. 셋째, 업계단체의 대응전략으로 미국통상에 관련된 최신정보를 신속히 수집하여 이를 파악하고 관련된 정보를 전달하는데 힘써야 한다. 그리고 통상마찰의 문제가 발생하기 전에 로비전략을 수립해 놓음으로써 시기적전하고 적당한 대처를 해 나갈 수 있다는 것이다. 업계의 전체의견을 미국의 정부, 의회, 동종 관련단체 등에 효과적으로 전달하기 위한 채널개발의 중요성과 해외경제 홍보센타(가칭)의 설치로 대규모 수출기업과 업계단체간의 해외홍보의 효율성을 올릴 수 있다. 넷째, 민간기업의 대응전략으로는 현지국과의 공존공영을 추구하여 현지국의 경제에 기여하겠다는 기업 시민의식과 현지국 사회활동에 적극 참여하여 한국의 대외 이미지 개선을 위한 적극적인 PR활동과 기업의 최고경영자 차원의 로비활동 추진으로 대미(對美)로비체제를 적극적이며 능동적으로 수행할 수 있도록 하여야 한다.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.263-270
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• 2021

Reinforcement learning(RL) is the method to find an optimal policy through training. and it is one of popular methods for solving lifesaving and disaster response problems effectively. However, the conventional reinforcement learning method for disaster response utilizes either simple environment such as. grid and graph or a self-developed environment that are hard to verify the practical effectiveness. In this paper, we propose the design of a disaster response RL environment which utilizes the detailed property information of the disaster simulation in order to utilize the reinforcement learning method in the real world. For the RL environment, we design and build the reinforcement learning communication as well as the interface between the RL agent and the disaster simulation. Also, we apply the dimension reduction method for converting non-image feature vectors into image format which is effectively utilized with convolution layer to utilize the high-dimensional and detailed property of the disaster simulation. To verify the effectiveness of our proposed method, we conducted empirical evaluations and it shows that our proposed method outperformed conventional methods in the building fire damage.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.1-7
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• 2023

The advent of deep learning technologies has led to the development of various medical applications, making healthcare services more convenient and effective. Among these applications, heart rate estimation is considered a vital method for assessing an individual's health. Traditional methods, such as photoplethysmography through smart watches, have been widely used but are invasive and require additional hardware. Recent advancements allow for contactless heart rate estimation through facial image analysis, providing a more hygienic and convenient approach. In this paper, we propose a lightweight methodology capable of accurately estimating heart rate in mobile environments, using a specialized 2-channel network structure based on 2D convolution. Our method considers both subtle facial movements and color changes resulting from blood flow and muscle contractions. The approach comprises two major components: an Encoder for analyzing image features and a regression layer for evaluating Blood Volume Pulse. By incorporating both features simultaneously our methodology delivers more accurate results even in computing environments with limited resources. The proposed approach is expected to offer a more efficient way to monitor heart rate without invasive technology, particularly well-suited for mobile devices.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.145-156
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• 2011

The study is to analyze voting behaviors revealed through the June 2 local elections, and to learn their implications by exploring and comparing the main factors that influence how to recognize and select a candidate. To achieve this, in-depth interviews have been conducted focusing on those who voted in the last election. The analysis shows that most respondents regard their political tendencies as moderate and make decisions on whom to vote for 2 to 3 days prior to election. It also indicates that what party candidates belong to is the highest motivation in deciding for whom to vote and they generally vote as they believe. According to the study, not only do the poll's results hardly affect their choice of candidates, but also the polls turn out significantly different from the actual results. The great gap between the polls and the actual outcome signifies that how to conduct a poll is wrong and people intend to conceal their opinions. While the media has had a decisive effect on the image of candidates, it is through promotional materials for political campaigns that the candidates' policy is recognized. The study also says that the Four-River is the most influential political issue in election. The study identifies voters' behavior specifically and in depth, and suggests some lessons to make use of for the future elections.