• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.841-846
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• 2010

This paper presents design and implementation of an intelligent video surveillance system. The proposed system has advantages of management efficiency and operation robustness unrelated to working condition compared to conventional CCTV based system. The system hardware is designed and implemented by using commercial chips such as digital media processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a infrared image and to detect disaster situation such as fire. The required functions are confirmed by testing of the prototype and we verified practicality of the system.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.134-140
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• 2021

Big data has recently been used in various industries such as tourism, medical care, distribution, and marketing. And it is evolving to the stage of collecting real-time information or analyzing correlations and predicting the future. In the tourism industry, big data can be used to identify the size and shape of the tourism market, and by building and utilizing a large-capacity database, it is possible to establish an efficient marketing strategy and provide customized tourism services for tourists. This paper has begun with anticipation of the effects that would occur when big data is actively used in the tourism field. Because the method of use must have applicability and practicality, the spatial scope will be limited to Seosan, Chungcheongnam-do, and research will be conducted. In this paper, to improve the quality of tourism courses by collecting and analyzing the number of mention data and sentiment index data on social media, which reflect the tourist's interest, preference and satisfaction. Therefore, it is used as basic data necessary for the development of new local tourism courses in the future. In addition, the development of tourism courses will be able to promote tourism growth and also revitalizing the local economy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.399-406
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• 2019

The variation of ground-penetrating radar(GPR) signal characteristics from dielectric-filled nonmetallic pipes buried in inhomogeneous ground are compared through a numerical simulation. The relative permittivity distribution of the ground is generated by using the continuous random media(CRM) technique. As a function of the relative permittivity of the material filling the nonmetallic pipe buried in the ground media, GPR signals are simulated by using the finite-difference time-domain(FDTD) method. We show that, unlike the case for homogeneous ground, the distortion characteristics of the reflected waves caused by the front convex surface and the rear concave surface of the pipe buried in inhomogeneous ground are different depending on the permittivity contrast between the inside and outside of the pipe.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.189-200
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• 2022

The gig economy offers many advantages, such as flexibility, variety, independence, and lower cost. However, there are also safety concerns, lack of regulations, uncertainty, and unsatisfactory services, causing people to voice their opinion on social media. This paper aims to explore the sentiments of consumers concerning gig economy services (Grab, Foodpanda and Airbnb) through the analysis of social media. First, Vader Lexicon was used to classify the comments into positive, negative, and neutral sentiments. Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. Results suggested that gig economy services in Malaysia received more positive sentiments (52%) than negative sentiments (19%) and neutral sentiments (29%). Based on the three algorithms used in this research, LGBM has been the best model with the highest accuracy of 85%, while SVM has 84% and LR 82%. The results of this study proved the power of text mining and sentiment analysis in extracting business value and providing insight to businesses. Additionally, it aids gig managers and service providers in understanding clients' sentiments about their goods and services and making necessary adjustments to optimize satisfaction.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1339-1347
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• 2021

Indonesia has a population of more than 260 million, of which, by 2020, Generation Y is predicted to account for 70% of the total. With different birth years, Generation Y is the backbone of Indonesia's product purchasing. Generation Y is interested in establishing strong relationships with specific brands on social media. They are also interested in working with companies to design a product. Most Generation Y utilizes more than one electronic device and they are also brand loyal. Therefore, this study seeks to examine the effect of social media (i.e., e-WOM, online community, and online advertising) on brand image and loyalty in Generation Y in Indonesia. The sampling method employed was purposive sampling. A total of 150 respondents in the age range of 23-30 years were involved as the sample. Using multiple regression model in data analysis, this study proved that e-WOM, not only have a positive and significant effect on the brand image, but also on brand loyalty. Furthermore, online community also positively and significantly affects brand image and brand loyalty. Likewise, online advertising has a positive and significant effect on brand image and brand loyalty. This study's findings indicated that all the proposed hypotheses were well accepted.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.437-450
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• 2022

Generative adversarial networks(GANs) have demonstrated remarkable success in image synthesis. However, since GANs show instability in the training stage on large datasets, it is difficult to apply to various application fields. A single image GAN is a field that generates various images by learning the internal distribution of a single image. In this paper, we investigate five Single Image GAN: SinGAN, ConSinGAN, InGAN, DeepSIM, and One-Shot GAN. We compare the performance of each model and analyze the pros and cons of a single image GAN.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.305-316
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• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

• Journal of Drive and Control
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• v.19 no.1
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• pp.62-68
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• 2022

Considering the characteristics of industrial machines that lack vehicle-induced wind, forced convection by a cooling fan is mostly required. Therefore, numerical analysis of an engine room is usually performed to examine the cooling performance in the room. However, most engine rooms consist of a number of parts and components at specific positions, leading to high costs for numerical modeling and simulation. In this paper, a new methodology for three-dimensional computer-assisted design simplification was proposed, especially for the pile of components and parts at the engine room outlet. A porous media model and regression analysis were used to derive a meta-model for imitating the flow rate reduction at the outlet by the pile. The results showed that the fitted model was reasonable considering the coefficient of determination. The final numerical model of the engine room was then used to simulate the velocity distribution by changing the mass flow rate at the outlet. The results showed that both velocity distributions were significantly changed in each case and the meta-model was valid in imitating the flow rate reduction by some piles of components and parts.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1305-1307
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• 2022

자동차 부품의 결함은 시스템 전체의 성능 저하 및 인적 물적 손실이 발생할 수 있으므로 생산라인에서의 불량 검출은 매우 중요하다. 따라서 정확하고 균일한 결과의 불량 검출을 위해 딥러닝 기반의 고장 진단 시스템이 다양하게 연구되고 있다. 하지만 제조현장에서는 정상 샘플보다 비정상 샘플의 발생 빈도가 현저히 낮다. 이는 학습 데이터의 클래스 불균형 문제로 이어지게 되고, 이러한 불균형 문제는 고장을 판별하는 분류 모델의 성능에 영향을 끼치게 된다. 이에 본 연구에서는 모터의 동작음으로부터 불량 모터를 판별하는 불량 검출 시스템 설계를 위한 데이터 불균형 해결 방법을 제안한다. 자동차 사이드 미러 모터의 동작음을 학습 및 테스트를 위한 데이터 셋으로 사용하였으며 손실함수 계산 시 학습 데이터 셋의 클래스별 샘플 수 가 반영되는 label-distribution-aware margin(LDAM) loss 와 Inception, ResNet, DenseNet 신경망 모델의 비교 분석을 통해 불균형 데이터를 처리할 수 있는 가능성을 보여주었다.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.342-364
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• 2014

The purpose of this paper is to provide an answer for the following question: What are the major shifts and implications of the unprecedently competitive and rapidly changing media ecosystem in the era of N-screen and OTT services? I've attempted to understand the complex and competitive nexus among media from an historical context by focusing on the displacement vs. complement thesis. The TPC model by Han has been employed for the analysis of the current dynamics of US media industries by triangulating three areas: Technology/industry, public policy and consumer/culture. More specifically, the US media landscape is initially divided into two competitive turfs - the competitors equipped with OTT services and the legacy media industry, and then the traditional media industry was grouped again into PayTV group(telecom service providers with IPTV and mobile TV, cable/Satellite TV networks) and Free (over-the-air) TV networks. Six major shifts were identified by the analysis: power shift in telecom carriers, power shifts in TV industry, Telecom/OTT partnership, time shifts, place shifts, and finally business model shifts.