• International journal of advanced smart convergence
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• v.13 no.1
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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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• v.13 no.1
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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.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.457-466
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• 2017

This study tries to figure out the communication types between a mother-in-law and a foreign daughter-in-law through their 'confrontational conversation.' For this, three episodes of 'Multicultural Mother-in-law and Daughter-in-law Biography' aired by EBS (Education Broadcasting System) were monitored. The dialogues between the mother-in-law and the foreign daughter-in-law were written down and analyzed. According to the result, there were 'dysfunctional communication' styles during their conversation. Theses styles deepened their conflict. Thus, to abate the conflict between the mother-in-law and the foreign daughter-in-law, this study suggested that it was necessary to develop the convergence counseling program and the family therapy for their functional communication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.99-105
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• 2015

This paper deals with the mMMA (modified MMA) which possible to improving the convergence speed that employing the serial connecting form of two stage digital filter instead of signal filter of MMA adaptive equalizer without applying the variable step size for compensates the intersymbol interference by channel distortion in the nonconstant modulus signal. The adaptive equalizer can be implemented by signal digital filter using the finite order tap delay line. In this paper, the equalizer is implemented by the two stage serial form and the filter coefficient are updated by the error signal using the same algorithm of MMA in each stage. The fast convergence speed is determined in the first stage, and the residual isi left at the output of first stage output is minimized in the second stage filter. The same digital filter length was considered in single stage and two stage system and the performance of these systems were compared. The performance index includes the output signal constellation, the residual isi and maximum distortion, MSE that is measure of the convergence characteristics, the SER. As a result of computer simulation, mMMA that has a FIR structure of two stage, has more good performance in every performance index except the constellation diagram due to equalization noise and improves the convergence speed about 1.5~1.8 time than the present MMA that has a FIR structure of single stage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.21-27
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• 2022

As society develops and becomes more complex, new and diverse types of disasters such as fine dust and infectious diseases are occurring. However, in the past, there was no PA(Public Address) system that provided accurate information to prepare for such a disaster. In this paper, we propose a public address system that automatically broadcasts an alarm by analyzing polluted air quality data collected from public data and IoT sensors. The warning level varies depending on the air quality, and the information provided by public data may show a significantly different result from the guide area due to various factors such as the distance from the measuring station or the wind direction. To compensate for this, we are going to propose a method for broadcasting by comparing and analyzing data obtained from public data and data from on-site IoT sensors.

• ETRI Journal
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• v.35 no.5
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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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• v.5 no.4
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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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• v.10 no.4
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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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• v.10 no.3
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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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• v.10 no.4
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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.