• International journal of advanced smart convergence
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• 제13권1호
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• pp.92-98
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• 2024

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.129-139
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• 2024

In digital marketing, the strategic use of emojis in social media advertising, particularly on the Xiaohongshu app, significantly influences consumer acceptance and purchase behavior. This study examines the impact of emoji-laden advertisements and the role of brand metaphorical warmth on consumer perceptions. Employing a tailored questionnaire, the research explores how emojis affect brand advertisement reception, filling a gap in empirical research on emoji advertising effectiveness. Findings indicate that emojis, when used judiciously, enhance consumer acceptance and contribute to a positive brand perception. However, excessive use may undermine trust. Brand metaphorical warmth emerges as a crucial factor, suggesting that emojis can effectively convey warmth, fostering a deeper emotional connection with consumers. These insights offer practical implications for refining social media marketing strategies, advocating for a balanced approach to emoji usage in advertisements to optimize engagement and influence consumer behavior.

• 디지털융복합연구
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• 제15권7호
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• pp.457-466
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• 2017

본 연구는 다문화 가정 내의 고부갈등을 심화시키는 '갈등대화'를 통해 다문화 가정 내의 고부 간 '의사소통'의 유형을 보기 위함이다. 이를 위해 3편의 EBS '다문화 고부열전' 에피소드를 모니터링 하고, 대화 내용을 기록하여 융복합적 분석을 하였다. 분석한 결과 다문화 가정 내의 고부 간 대화에서 '역기능적 의사소통' 유형이 나타났으며, 이런 의사소통의 유형은 고부갈등을 더욱 심화시키고 있었다. 따라서 다문화 가정 내 고부갈등을 완화하기 위해서 순기능적 의사소통을 위한 융복합적 상담 프로그램 개발 및 가족 상담 필요성을 제언하였다.

• 한국인터넷방송통신학회논문지
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• 제15권3호
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• pp.99-105
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• 2015

본 논문에서는 nonconstant modulus 신호를 대상으로 채널의 찌그러짐에 의한 부호간 간섭을 보상하기 위한 MMA (Multiple Modulus Algorithm) 적응 등화기를 가변 적응 스텝 크기를 적용하지 않고 2단의 직렬 연결 형태로 구현하여 수렴 속도를 개선할 수 있는 mMMA (modified MMA)에 대하여 다룬다. 적응 등화기는 유한 차수의 탭 지연선에 의한 단일 디지털 필터로 구현되므로, 논문에서는 이를 2단의 직렬 연결 필터로 구현한 후 각 단에서는 MMA와 동일한 알고리즘으로 오차 신호를 얻은 후 필터 계수를 갱신하게 된다. 따라서 첫단에는 빠른 수렴 속도를 결정하며, 두 번째단에서는 첫단의 출력에 포함되어 있는 잔류 isi양을 최소화시키도록 탭 계수를 갱신한다. 이때 1단 시스템과 2단 시스템은 동일한 차수의 필터가 되도록 조정하면서 적응 등화 성능을 비교하였으며, 성능 비교를 위한 지수로는 등화기 출력 신호 성상도, 수렴 특성을 나타내는 잔류 isi, 최대 찌그러짐과 MSE, 채널의 신호대 잡음비에 따른 SER을 사용하였다. 시뮬레이션 결과 2단의 FIR 구조를 갖는 mMMA가 1단의 기존 MMA보다 등화 잡음에 의한 성상도를 제외한 모든 성능 지수에서 우월하며, 수렴 속도는 1.5~1.8배 정도 개선됨을 확인하였다.

• 한국인터넷방송통신학회논문지
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• 제22권1호
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• pp.21-27
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• 2022

사회가 발전하고 복잡해짐에 따라 재난의 종류도 미세먼지, 전염병 등과 같이 새롭고 다양하게 발생하고 있다. 하지만 기존에는 이러한 재난에 대비할 수 있는 정확한 정보를 제공하는 전관방송 시스템이 없었다. 본 논문에서는 공공 데이터와 IoT 센서로부터 수집된 오염된 대기질 데이터를 분석하여 자동으로 경보를 방송하는 전관방송 시스템을 제안한다. 대기질에 따라 경보의 단계가 달라지며, 공공데이터에서 제공하는 정보는 측정소로부터의 거리나 풍향 등 다양한 요인으로 인해 안내 지역과 상당한 차이가 있는 결과를 나타내기도 한다. 이를 보완하기 위해 공공데이터에서 가져온 데이터와 현장 IoT센서에서 얻은 데이터를 비교 분석하여 방송하는 방법을 제안하고자 한다.

• ETRI Journal
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• 제35권5호
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• pp.943-946
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• 2013

Instead of the extended Kalman filter, the unscented Kalman filter (UKF) has been used in nonlinear systems without initial accurate state estimates over the last decade because the UKF is robust against large initial estimation errors. However, in a multirate integrated system, such as an inertial navigation system (INS)/Global Positioning System (GPS) integrated navigation system, it is difficult to implement a UKF-based navigation algorithm in a low-grade or mid-grade microcontroller, owing to a large computational burden. To overcome this problem, this letter proposes a modified UKF that has a reduced computational burden based on the basic idea that the change of probability distribution for the state variables between measurement updates is small in a multirate INS/GPS integrated navigation filter. The performance of the modified UKF is verified through numerical simulations.

• International journal of advanced smart convergence
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• 제5권4호
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• pp.40-47
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• 2016

Journalism robot by using a computer algorithm, while maintaining the precision and reliability of the existing media refers to an article which is automatically created. In this paper, we introduce 'stock robot' of robot journalism which writes securities articles and describe artificial intelligence algorithms in stages. Key steps of stock robot implemented artificial intelligence algorithm through four steps of data collection and storage, key event extraction, article content production, and article production. This research has developed a stock robot that collects and analyzes data on social issues and stock indexes for the last 2 years. In the future, as the algorithm is further developed, it becomes possible to write securities articles quickly and accurately through social issues. It will also provide customized information tailored to the user's preferences.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.59-65
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• 2021

In this paper, we propose the AI certification standardization activities for systematic research and planning for the standardization of trustworthy artificial intelligence (AI). The activities will be in two-fold. In the stage 1, we investigate the scope and possibility of standardization through AI reliability technology research targeting international standards organizations. And we establish the AI reliability technology standard and AI reliability verification for the feasibility of the AI reliability technology/certification standards. In the stage 2, based on the standard technical specifications established in the previous stage, we establish AI reliability certification program for verification of products, systems and services. Along with the establishment of the AI reliability certification system, a global InterOp (Interoperability test) event, an AI reliability certification international standard meetings and seminars are to be held for the spread of AI reliability certification. Finally, TAIPP (Trustworthy AI Partnership Project) will be established through the participation of relevant standards organizations and industries to overall maintain and develop standards and certification programs to ensure the governance of AI reliability certification standards.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.