• Smart Media Journal
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• v.5 no.1
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• pp.95-103
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• 2016

This study aims to consider the action plans to make the industry of Korean design consultancies accomplish qualitative growth by comparing the operation characteristics of design consulting firms between Korean design firms and American ones. For this, questionnaire survey and comparison analysis was performed for the operation characteristics of 109 Korean design firms and 97 American ones. The analysis results shows that operation characteristics of Korean design firms comparing to those of American ones keep low in all 7 areas of building long-term partnership relationship, building multi- disciplinary organization, utilizing result-based compensation system, developing design at the strategic business level of clients, executing active design business, making convergent networking with other industry and performing specialized design services. In order to accomplish stable industry infrastructure of design consulting industry with qualitative growth, it requires continuous effort to execute 7 operation characteristics of Korean design firms.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.

• Smart Media Journal
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• v.13 no.4
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• pp.23-32
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• 2024

Large-scale fires and their consequential damages are becoming increasingly common, but confidence in fire detection systems is waning. Recently, widely-used chemical fire detectors frequently generate lots of false alarms, while video-based deep learning fire detection is hampered by its time-consuming and expensive nature. To tackle these issues, this study proposes a fire detection model utilizing an autoencoder approach. The objective is to minimize false alarms while achieving swift and precise fire detection. The proposed model, employing an autoencoder methodology, can exclusively learn from normal data without the need for fire-related data, thus enhancing its adaptability to diverse environments. By amalgamating data from five distinct sensors, it facilitates rapid and accurate fire detection. Through experiments with various hyperparameter combinations, the proposed model demonstrated that out of 14 scenarios, only one encountered false alarm issues. Experimental results underscore its potential to curtail fire-related losses and bolster the reliability of fire detection systems.

• Smart Media Journal
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• v.13 no.8
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• pp.58-66
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• 2024

Nitrogen oxides(NOx) in coal-fired power plants are significant contributors to air pollution, influencing the formation of ozone and fine particulate matter, thereby adversely affecting health. Therefore, accurate prediction of NOx emissions is essential. Existing researches have mainly performed based on off-line learning methods, leading to poor prediction performance with the limited training dataset. This paper proposes the online learning model of online support vector regression to predict NOx emissions from coal-fired power plants. Online learning model, which updates a model whenever new observations come out, demonstrates high prediction accuracy even when initial data is scarce. The experimental results showed that the performance of online learning prediction was better than existing off-line learning methods. The results indicated online learning method is a valuable tool for predicting NOx emissions, especially in situations where initial data is limited and data is continuously updated in real-time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.69-70
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• 2019

4차 산업혁명 시대의 핵심 기술 분야라고 불리는 가상현실(Virtual Realityl VR)/증강현실(Augmented Reality; AR) 기술은 그 동안 IT 시장을 주도해 온 스마트폰 시장이 포화상태에 도달함에 따라 주요 IT기업들의 차세대 비즈니스로 떠오르고 있으며, 미디어 플랫폼인 VR에 대한 연구 또한 계속해서 진행되고 있다. 또한 최근 들어 디스플레이 해상도가 높아지고 PC의 성능이 좋아지면서 많은 회사에서 VR 콘텐츠에 대응하여 VR기기를 출시하고 있다. 하지만 아직까지 VR에 대한 호환성 테스팅 방법은 제대로 제시되지 않고 있는 실정이다. 따라서 본 논문에서는 연구를 통해서 효과적이고 효율적인 호환성 테스트 방법을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.525-529
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• 2015

Depending on the field of smart industry has become increasingly widespread, the digital signage industry as advertising and content industry is emerging. However, this industry is growing rapidly it is not the reason for that is lack of a legal definition or system. The current legal system merely existing laws that apply to the use of outdoor advertising such as advertising and outdoor advertising Electrical, according to a separate law on digital signage is still is not enough. Most of the current legal system between a size that it is put in the control object, its type, the installation location and details and locations of areas in accordance with the regulation member of the law which can reduce the effectiveness of such a business to control them collectively There is concern that the differences are caused by unification can be difficult. In reality, the institutions of the new law was necessary, organized under the existing regulation rather than promoting new laws to screen the effectiveness of the national business media industry through a kind of standardization and unification of the digital signage industry in the future creation of a jurisdiction other than safety administration Science It is important to foster.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.189-196
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• 2011

As internet is getting advanced day by day, digital contents have been developed in various areas as killer content in the IT industry. It needs to develop lots of complicated digital content protect systems due to the enhancement and variety of user's multimedia devices. Although there are lots of protect systems based on DRM(Digital Rights Management) technology, it is difficult to provide secure protection because of the problems resulting from analog hole problem, inefficiency of key sharing and various independent protect technologies. Thus, in this paper, we propose a novel authentication and protect system based on RFID(Radio Frequency Identification) technology to solve the problems and show possibility of free content duplication and efficient contents management in smart home environments.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.367-373
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• 2019

As the number of Battery Electric Vehicle (BEV) is increasing dramatically Vehicle-to-Grid (V2G) te chnology also has been spotlight from industry and academia recently. With help of V2G technology Battery of EV can play many important roles like as energy storage system (ESS) and electric energy resource in Smart Grid environment. This paper provides comprehensive review of Vehicle-to-Home(V2H), Vehicle-to-Building(V2B) and Vehicle-to-Grid(V2G) technologies. The economical analysis of these technologies is also discussed.

• Smart Media Journal
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• v.11 no.11
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• pp.40-48
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• 2022

In this paper, an educational kit that can be used in AI education was developed to solve the difficulties of AI education. Through this, object detection and person detection in computer vision using CNN and OpenCV to learn practical-oriented experiences from theory-centered and user image recognition (Your Own) that learns and recognizes specific objects Image Recognition), user object classification (Segmentation) and segmentation (Classification Datasets), IoT hardware control that attacks the learned target, and Jetson Nano GPIO, an AI board, are developed and utilized to develop and utilize textbooks that help effective AI learning made it possible.

• Smart Media Journal
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• v.13 no.3
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• pp.27-35
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• 2024

This study deals with a method of combining image generation using Semi Supervised Learning based on GAN (Generative Adversarial Network) and image classification using ResNet50. Through this, a new approach was proposed to obtain more accurate and diverse results by integrating image generation and classification. The generator and discriminator are trained to distinguish generated images from actual images, and image classification is performed using ResNet50. In the experimental results, it was confirmed that the quality of the generated images changes depending on the epoch, and through this, we aim to improve the accuracy of industrial accident prediction. In addition, we would like to present an efficient method to improve the quality of image generation and increase the accuracy of image classification through the combination of GAN and ResNet50.