• International journal of advanced smart convergence
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• 제12권3호
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• pp.200-210
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• 2023

Until now, it is popular to use question-and-answer-based for human personality. The current inspection of representative personality types includes Myers-Briggs Type Indicator (MBTI) and job suitability evaluations. The problem of these inspection methods is influenced by the user's environment and psychological status during MBTI inspection. To solve this problem, we proposed MBTI Identification Model based on measuring bioelectricity patterns. We adapt traditional Korean medicine, the Eight Constitution, to this model. We develop an automatic MBTI identification algorithm that maps the Eight Constitution via biological current patterns to identify MBTI personality types. By utilizing the algorithm proposed in this research, it is anticipated that users will be able to measure MBTI more easily and accurately.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.49-58
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• 2020

Non-orthogonal multiple access (NOMA) has been recognized as a significant technology in the fifth generation (5G) and beyond mobile communication, which encompasses the advanced smart convergence of the artificial intelligence (AI) and the internet of things (IoT). In NOMA, since the channel resources are shared by many users, it is essential to establish the user fairness. Such fairness is achieved by the power allocation among the users, and in turn, the less power is allocated to the stronger channel users. Especially, the first and second strong channel users have to share the extremely small amount of power. In this paper, we consider the power optimization for the two users with the small power. First, the closed-form expression for the power allocation is derived and then the results are validated by the numerical results. Furthermore, with the derived analytical expression, for the various channel environments, the optimal power allocation is investigated and the impact of the channel gain difference on the power allocation is analyzed.

• ETRI Journal
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• 제31권2호
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• pp.193-200
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• 2009

In this paper, we study the performance of subspace-based multiuser detection techniques for multicarrier code-division multiple access (MC-CDMA) systems. We propose an improvement in the PASTd algorithm by cascading it with the classical Gram-Schmidt procedure to orthonormalize the eigenvectors after their sequential extraction. The tracking of signal subspace using this algorithm, which we call OPASTd, has a faster convergence as the eigenvectors are orthonormalized at each discrete time sample. This improved PASTd algorithm is then used to implement the subspace blind adaptive multiuser detection for MC-CDMA. We also show that, for multiuser detection, the complexity of the proposed scheme is lower than that of many other orthogonalization schemes found in the literature. Extensive simulation results are presented and discussed to demonstrate the performance of the proposed scheme.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.154-163
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• 2023

With the rapid development of AI technology, ChatGPT and other AI content creation tools are becoming common, and users are becoming curious and adopting them. These tools, unlike search engines, generate results based on user prompts, which puts them at risk of inaccuracy or plagiarism. This allows unethical users to create inappropriate content and poses greater educational and corporate data security concerns. AI content detection is needed and AI-generated text needs to be identified to address misinformation and trust issues. Along with the positive use of AI tools, monitoring and regulation of their ethical use is essential. When detecting content created by AI with an AI content detection tool, it can be used efficiently by using the appropriate tool depending on the usage environment and purpose. In this paper, we collect data on AI content detection tools and compare and analyze the functions and characteristics of AI content detection tools to help meet these needs.

• 한국인터넷방송통신학회논문지
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• 제13권1호
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• pp.27-34
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• 2013

본 논문은 시분산 통신 채널에서 부호간 간섭을 수신측에서 경감시키기 위하여 사용되는 CCA (Compact Constellation Algorithm) 적응 등화 알고리즘의 성능을 비교하였다. 이 알고리즘은 기본적으로 CMA 등화기의 위상 미복원 문제를 해결하기 위하여 등장하였으며 DDA(Decision Directed Algorithm)와 RCA(Reduced Constellation Algorithm)의 개념을 조합하였다. DDA는 단일 레벨 신호에 대해서는 안정된 수렴 특성을 갖지만 다중 레벨의 수가 큰 QAM 신호에 대해서는 매우 불안한 문제점을 가지며, RCA는 초기 수렴 상태가 보장되지 않거나, 수렴후 안정 상태에서 misadjustment에 의한 등화 잡음이 DDA보다 큰 문제점이 있으므로, 이와 같은 점들을 개선하기 위해 CCA 적응 등화 알고리즘이 등장하였다. CCA 적응 등화 알고리즘의 성능 분석을 위하여 컴퓨터 시뮬레이션을 수행하였으며, 이를 위해 수신측에서의 등화기 출력 신호인 복원된 신호 성상도, 잔류 isi와 MD (Maximum Distortion) 곡선에 의한 수렴 특성 및 SER (Symbol Error Rate) 성능을 DDA, RCA와 비교하였다. 시뮬레이션 결과 모든 성능 지수에서 DDA가 가장 우월하였지만 수렴이 보장되지 않으며, 멀티 레벨 신호에서의 불안정성이 있으므로 이를 해결할 수 있는 CCA가 RCA보다 우월한 성능을 가짐을 확인하였다.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.159-165
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• 2019

'4th Industrial Revolution' is accelerating as a core part of creating new growth engines and enhancing competitiveness of businesses. The fourth industrial revolution means the transformation of society and industries that are brought by IoT (Internet of Things), big data analysis, AI (Artificial Intelligence), and robot technology. Information and Communication Technology (ICT), which is a major factor, is affecting production and manufacturing systems and as ICT technologies become more advanced, intelligent information technology is generally utilized in all areas of society, leading to hyper-connected society where new values are created and developed. ICT technology is not just about connecting devices and systems and making smart, it is about constantly converging and harmonizing new technologies in a number of fields and driving innovation and change. It is no exception to the agro-fisheries trade. In particular, ICT technology is applied to the agricultural sector, reducing labor, providing optimal environment for crops, and increasing productivity. Due to the nature of agriculture, which is a labor-intensive industry, it is predicted that the ripple effects of ICT technologies will become bigger. We are expected to use the Smart Concentration using ICT convergence technology as a useful resource for changing smart farms, and to help develop new service markets.

• 한국인터넷방송통신학회논문지
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• 제14권4호
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• pp.181-186
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• 2014

기업도 집단지성에 의한 지식 공유 및 외부와의 협력을 통한 지식의 생산/공유가 중요하다. 따라서 지식경영 시스템도 SNS 기반으로 설계하고 구축한 차세대 지식경영 시스템 도입이 필요하다. 본 논문에서는 기존 지식경영 시스템을 조사분석하여 문제점을 분석하고 지식경영 패러다임의 변화와 새로운 지식경영 시스템의 요구사항을 알아보았다. 새로운 지식경영 시스템의 요구사항인 집단지성, 오픈이노베이션, IT 기술과의 융합을 고려하여 볼 때 차세대 KMS로는 SNS 기반 지식경영시스템이 가장 적합하다. 그러므로 새로운 차세대 지시경영시스템의 서비스 구조와 SNS기반의 지식경영시스템의 메인 설계 및 지식톡 설계 등을 통하여 SNS 기반 지식경영시스템의 구축 방법을 제시하고자 한다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.1-8
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• 2020

This paper studied a method of estimating target information using a radar in wireless communication. Position information on the target can be estimated angle, distance and velocity. The velocity information can be estimated since the Doppler frequency is changed in the moving target. The signal incident on the receiving array antenna is multiplied by the delay time and the reference signal to represent the output signal. This output signal is estimated by applying FFT (Fast Fourier Transform) after calculating signal correlation through correlation integrator. Since the output signal must be calculated within the correlator, it should be processed with the Dwell time. The correlation signal of the correlation integrator outside this Dwell time is indicated by the velocity measurement error. The FFT is applied to the signal that has passed through the correlated integrator in order to estimate the distance of the signal. The Doppler resolution must be improved because the FFT estimates target information using the Doppler information. The Doppler resolution decreases with increasing the integration time. The velocity information estimation should have no spread of the velocity. As a result of the simulation, there was no spread of the target velocity in this study.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.125-130
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• 2020

At the end of 1997, the volatility of the exchange rate intensified as the nation's exchange rate system was converted into a free-floating exchange rate system. As a result, managing the exchange rate is becoming a very important task, and the need for forecasting the exchange rate is growing. The exchange rate prediction model using the existing exchange rate prediction method, statistical technique, cannot find a nonlinear pattern of the time series variable, and it is difficult to analyze the time series with the variability cluster phenomenon. And as the number of variables to be analyzed increases, the number of parameters to be estimated increases, and it is not easy to interpret the meaning of the estimated coefficients. Accordingly, the exchange rate prediction model using artificial neural network, rather than statistical technique, is presented. Using DNN, which is the basis of deep learning among artificial neural networks, and LSTM, a recurrent neural network model, the number of hidden layers, neurons, and activation function changes of each model found the optimal exchange rate prediction model. The study found that although there were model differences, LSTM models performed better than DNN models and performed best when the activation function was Tanh.

• 방송공학회논문지
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• 제12권5호
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• pp.401-413
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• 2007

디지털 기술이 21세기의 인간 커뮤니케이션 패러다임을 변화시키고 있는 시점에서, 대한민국은 2005년 세계 최초로 DMB(Digital Multimedia Broadcasting) 서비스를 시작하였다. 이를 통해 기존 방송의 공간적 한계를 극복하여 이동 중에 시청이 가능할 뿐만 아니라, 다양한 디지털 기기와의 융합을 통해 쌍방향 커뮤니케이션이 가능한 뉴미디어의 시대가 펼쳐진 것이다. 하지만 신개념의 획기적인 퍼스널 미디어인 DMB가 아직 진부한 콘텐츠와 결합되어 있다. 이러한 문제는 특히 영화와 비디오 채널에서 더욱 심각한 상황인데, 여기서는 대부분 극장용 장편영화와 TV 드라마의 재전송이 이루어지고 있기 때문이다. 본 논문은 바로 이 미디어와 콘텐츠간의 '부'적합성을 지적하고, 그 대안으로서 디지털 초단편 영상을 디지털시대에 철저히 이동성과 개인성을 강조한 DMB를 위한 새로운 킬러콘텐츠로 제안하고자 한다.