• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.524-532
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• 2021

Smart TV is rapidly growing with the provision of OTT services, and has become an alternative to pay-TV services. Yet smart TV in Korea has been diffused slowly, and thus few research has paid attention to smart TV. With the global growth trend of smart TV, research on smartTV, focusing on users' characteristic and their behaviors, is critical to explain smart TV's usage. To employ the Mediapanel dataset, this study explores the impact of smart TV users' demographic factors and their pay-tv usage on smart TV usage. The results suggested that age, the type of household, household income, and market size are associated with smart TV usage. Pay-TV usage, specifically IPTV subscription and VOD expenses, have impacts on smart TV usage. Lastly the interaction effect between IPTV subscription and movie VOD expenses, has negatively associated with smart TV usage. This study may bring to re-attention to smart TV and to give insights into the industry field.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.1-6
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• 2021

In recent years, many people are living in a space limited by rapid global industrial development and economic growth, and rapid urbanization is underway, with the global urban population estimated to be more than 70 percent in 2050. Due to rapid urbanization, government-led smart city models are being developed and introduced to solve various urban problems such as disaster safety, air pollution, water pollution, energy shortage, disease, crime and transportation. However, since ICT technology of public housing is being developed as a type of social overhead capital project, it is necessary to develop micro-smart city projects that residents can feel by developing services such as public safety, living environment, living welfare, and energy management for public housing residents. Therefore, in this paper, the smart platform model of public housing for smart city in the era of the Fourth Industrial Revolution is planned and presented.

• Smart Media Journal
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• v.11 no.8
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• pp.55-64
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• 2022

In the recent education market, Edutech technology, in which various digital technologies are grafted into the education, is being actively applied due to the 4th industrial revolution and the development of ICT. In particular, realistic experiential learning contents that can provide realistic and immersive learning in a virtual space are in the spotlight and are being expanded to each field. However, in the field of Korean medicine education, the introduction of ICT is delayed due to the nature of Korean medicine, difficulties in apprenticeship education, quantitative education, and the absence of an objective evaluation system. Therefore, in this study, we propose a digital technology application for acupuncture and acupuncture points, where practice is particularly important in Korean medicine. Various methods of acupuncture and acupoints education using AR, MR, IoT and Touch-Display Table will provide an opportunity to change the paradigm of Korean medicine education and further contribute to the globalization of Korean medicine.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.1-7
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• 2021

Recently, technological differentiation(sensor, AI) of products using IoT technology to satisfy consumer needs in the mature market for smart home appliances has received a lot of positive responses. However, air conditioner products are in the early stages of convergence technology. Therefore, air conditioner products are fields that require ICT technologies for information production, collection, processing, storage, and service development beyond IoT. In this paper, we collect and store contactless bio-signal using IR-UWB radar technology. The blowing direction of the air conditioning is controlled according to bio-signal and user's sleep is monitored to provide an optimal sleep environment. In addition, we propose a service algorithm that can provide comfort with changes in the optimal conditions of air conditioning and emotional lighting depending on the discomfort index environment. Through this study, we developed an intelligent smart air conditioning service platform with ICT technology of bio-signal, discomfort index, and emotional lighting.

• KNOM Review
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• v.23 no.1
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• pp.1-9
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• 2020

With the rapid development of science and technology in recent years, the network environment are growing, and a huge amount of traffic is generated. In particular, the development of 5G networks and edge computing will accelerate this phenomenon. However, according to these trends, network malicious behaviors and traffic overloads are also frequently occurring. To solve these problems, network administrators need to build a network management system to implement a high-speed network and should know exactly about the connection topology of network devices through the network management system. However, the existing network topology discovery method is inefficient because it is passively managed by an administrator and it is a time consuming task. Therefore, we proposes a method of network topology discovery according to the amount of in and out network traffic. The proposed method is applied to a real network to verify the validity of this paper.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.17-24
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• 2022

Mobile malicious apps are increasing rapidly, and Android, which accounts for most of the global mobile OS market, is becoming a major target of mobile cyber security threats. Therefore, in order to cope with rapidly evolving malicious apps, there is a need for detection techniques of malicious apps using machine learning, one of artificial intelligence implementation technologies. In this paper, we propose a selected feature method using feature selection and feature extraction that can improve the detection performance of malicious apps. In the feature selection process, the detection performance improved according to the number of features, and the API showed relatively better detection performance than the permission. Also combining the two characteristics showed high precision of over 93% on average, confirming that the appropriate combination of characteristics could improve the detection performance.

• Korea Trade Review
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• v.41 no.3
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• pp.177-198
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• 2016

China has retained economic growth rate of average 9% for more than ten years recently after China introduced capitalistic market economy system in 1979 by Deng Xiaoping. China has attracted foreign direct investment for a long time because it has retained very high economic growth rate, low labor cost, and various policies for foreign investors. This paper tries to analyse the determinants of foreign direct investment inflow after reform-opening of China with empirical analysis methods utilizing each province·city's specific characteristics by using the panel data from 1985 to 2013. For the empirical analysis we use random effect model, fixed effect model, pooled OLS, and random coefficient model. The results by pooled OLS and random coefficient model are presented for the comparison with the main results in the process of research. The research shows the results by fixed effect model are better than those by random effect model after doing Hausman's test. The results shows that GRDP, capital stock, and telecommunication exert a positive relationship with foreign direct investment, while express way variable exerts a negative one. China's education level surprisingly does not attract foreign direct investment even though it is not at a critical level. Therefore, the Chinese government should try to increase national income level as it symbolizes market size; encourage domestic investment; and construct high quality telecommunication infrastructure.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.249-251
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• 2020

본 논문에서는 코로나바이러스감염증19 사태가 국내 취업시장에 어떠한 영향을 미쳤는지에 대해 알아보기 위하여 빅데이터를 활용한 직업 관련 분석 및 시각화를 수행하였다. 빅데이터를 위한 기본 자료는 통계청 자료와 워크넷 Open API를 활용하였으며, 빅데이터 처리 과정을 거쳐 결과값을 예측을 시도하였다. 2020년도 워크넷 Open API를 통해 고용수와 통계청 자료를 통해 비교 분석 및 시각화를 실시하였고, 08년~20년 취업자수를 통해 시계열 분석 및 예측을 진행해 앞으로의 횡보를 예상해보았다. 분석한 결과 19년, 20년도를 비교 분석했을 때에는 크게 차이가 나지 않았다. 추가적으로 시계열 분석기법을 활용해 보았을 때 매년 고용수는 전체적으로 증가하고 4월에는 감소, 7월에는 증가하는 추세가 나왔다. 코로나바이러스감염증19 사태로 인해 공공기관과 언택트 시대에 따른 화상회의나 재택근무로 인해 운수·통신 취업률은 상승한다는 결과값이 도출되었고, 자영업이나 서비스 직업 등은 다른 직종에 비해 큰 감소를 보여줬으나 국가 경제 활성화에 따른 고용수는 점차 증가할 것이라 예측된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.380-380
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• 2020

가뭄 피해 극복을 위한 인공 함양지 통합관리시스템의 일부로써 지표수-지하수 연계 특성 분석용 의사결정을 전달하는 인공지능 스마트 계측기의 필요성이 꾸준히 제기되어 왔으나 실용성과 효율성을 동시에 갖춘 계측기는 시장에 출시되지 않았다. 기존의 계측기는 단순 측정이 목적이었으며 분석을 위해서는 일정 기간 직접 계측하여 분석하거나, 계측데이터를 원격 망을 통하여 서버로 전송하고 관리자가 데이터를 해석하는 방식을 취하였다. 또한, 수질 계측과 수질의 미소 변동성을 동시에 계측하여 수질 변화상태를 판단 할 수 있는 수질 계측기는 상품화되지 않아 다목적 수질 분석에 한계점을 갖고 있다. 이러한 한계점이 기존의 지하수 수질 계측기로는 불가능한 수중 라돈을 채수 없이 계측 가능하도록 하고, 순간 수질 변화 및 수질 변화 요인분석이 가능한 계측을 위하여 라돈, 전도도, 수위, 수온 및 필름형 pH 센서를 개발하여 적용한 다항목 계측기로 통합하는 연구가 필요한 이유이다. 개발한 계측기는 빅데이터 기반의 지능형 수질 변동성 분석 알고리즘을 내장하고 수직 깊이 방향의 다중심도 계측이 가능하도록 핵심적인 통신 연결성을 확보하였고 다양한 수질에서 견딜 수 있으며 특히 인공함양에서 발생하는 철, 망간에 부식되지 않는 재질을 이용하여 설계한 '지표수-지하수 연계 특성 분석용 다심도 및 인공지능 스마트 계측장치'이다. 본 장치는 기존 지하수 수질 계측기에서는 불가능하였던 순간 수위변화 및 수위변화 요인분석이 가능한 계측을 위하여 초당 측정 샘플링 주파수(10Hz)를 높인 계측회로를 개발하여 적용하였다.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.