• Food Science and Industry
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• v.54 no.3
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• pp.160-170
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• 2021

A recent advance in communication technologies accelerates the spread of food safety issues once presented by the news media. To respond to those safety issues and take steps in a timely manner, automatically detecting related information from the news data matters. This work presents an AI-based system that detects risk information within a food-related news article. Experts in food safety areas participated in labeling risk information from the food-related news articles; we acquired 43,527 articles in which food names and risk information are marked as labels. Based on the news document, our system automatically detects food names and risk information by analyzing similarities between words within a text by leveraging learned word embedding vectors. Our AI-based system shows higher detection accuracy scores over a non-AI rule-based system: achieving an absolute gain of +32.94% in F1 for the food name category and +41.53% for the risk information category.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.623-632
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• 2019

Many researches have been carried out for brightness and contrast enhancement, illumination reduction and so forth. Recently, the aforementioned hand-crafted approaches have been replaced by artificial neural networks. This paper proposes a convolutional neural network that can replace the method of generating a reflectance image where illumination component is attenuated. Experiments are carried out on 102 low-light images and we validate the feasibility of the replacement by producing satisfactory reflectance images.

• The Plant Pathology Journal
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• v.35 no.5
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• pp.417-424
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• 2019

Melanose, caused by Diaporthe citri, is one of severe diseases in citrus, a major economic resource in Jeju island. To reduce the usage amount of organic synthetic fungicide, bio-sulfur was tested as an alternative chemical to control citrus melanose in the present study. Direct antifungal activity of bio-sulfur against D. citri was determined through in vitro experiment using artificial nutrient media. Disease severity of melanose on bio-sulfur pretreated citrus leaves was lower than that on untreated ones. To illustrate the mechanism of disease suppression by bio-sulfur, infection structures were observed with a fluorescent microscope and a scanning electron microscope. In fluorescent microscopic observation, most conidia rarely germinated. In addition, hyphal growth on leaves pretreated with bio-sulfur was inhibited compared to that on untreated ones. In scanning electron microscope images of bio-sulfur pretreated leaves, surfaces of most conidia were shrunk while hyphae were morphologically changed and frequently branched. Such microscopic observations were also found for leaves pretreated with a commercial fungicide Dithianon. These results suggest that bio-sulfur may be used to control citrus melanose as an environment friendly alternative to organic synthetic fungicides

• Journal of Industrial Convergence
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• v.13 no.1
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• pp.41-47
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• 2015

The purpose of this study was to investigate how environment-friendly activities through nature affects attitude of children. 5-6 years old children were targeted for study from March to December, 2014. Rapid changes of modern society made increase of female workers and their participation rates in economic activity which results children to play more time with artificial toys and media. There are 3 stages to investigate effects. $1^{st}$ stage is to know about woods by visiting woods and experience environment-friendly activity. $2^{nd}$ stage is to experience woods with 5 senses not only in real woods but also in classroom. Lastly $3^{rd}$ stage is to make art work with natural object and make woods in classroom. Changes of hildren's attitude and view toward to the nature were recorded and analyzed by anecdotes perpetual inventory and environment-friendly attitude examination. By analysis of infant gives you the opportunity to encounter nature, often in conjunction with ongoing enjoys nature-friendly program in the classroom to play with toys, rather than a complete natural objects gradually formalized when presenting a natural, concentrated than the previous game this time is enhanced and creativity through nature through the promotion doeeojim and attitude to nature is also eco-friendly activities byeonhwadoem program showed that the impact on the attitude of the infant.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.87-96
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• 2019

Improvement of low-light image mainly focuses on the contrast enhancement. Many researches have been carried out for brightness enhancement, contrast improvement and illumination reduction. Recently, the aforementioned approaches have been replaced by artificial neural networks. This paper proposes a methodology that can replace the Retinex-based reflectance image acquisition by deep neural network. Experiments carried out on 102 low-light images validated the feasibility of the replacement by producing PSNR=30.8682(db) and SSIM=0.4345.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.77-84
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• 2022

The study highlights the features and trends of digital marketing for international business. To achieve these goals, the authors used a systematic approach that allows a comprehensive approach to the object of study, as well as used general and specific methods of scientific knowledge on the application of digital marketing for international business. The dynamics of the number of users of social networks in the world is analyzed, which allowed us to conclude about the steady trend of increasing the number of users of the Internet and social networks, as well as the time spent by users on social networks. The study of the dynamics of the number of users of social networks provides increased efficiency in the use of digital marketing tools to enhance international business. The most effective digital marketing tools for international business, including artificial intelligence, conversational marketing, chatbots, personalization, video marketing, live shopping, social media stories, interactive content, omnic marketing, augmented reality and technology immersion, native advertising, green marketing and mobile commerce.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.70-80
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• 2022

With the rapid growth in media service platforms providing broadcast programs or content services, content production has become more important and competitive. As a strategy to meet the diverse needs of global consumers for a variety of content and to retain them as long-term repeat customers, global over-the-top service providers are increasing not only the number of content productions but also their production efficiency. Moreover, a considerable amount of scene composition in the flow of content production work appears to be combined with rendering technology from a game engine and converted to object-based computer programming, thereby enhancing the creativity, diversity, quality, and efficiency of content production. This study examines the latest technology trends in content production such as virtual studio technology, which has emerged as the center of content production, the use cases in various fields of artificial intelligence, and the metadata standards for content search or scene composition. This study also examines the possibility of using object-based computer programming as one of the future candidate technologies for content production.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.703-717
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• 2022

Metaverse provides a simulated environment that can produce various values while conducting economic, social, and cultural activities in a digital society where the virtual and real worlds are connected. In this paper, the direction of technological progress is predicted by analyzing the characteristics of Metaverse services and their businesses. Technologies and latest researches for the realization of the Metaverse service platform are also explored. In addition, Metaverse Ethics to construct a sustainable Metaverse and Metaverse UX to increase users' service participation are also discussed. Moreover, the R&D promotion strategy for Metaverse services are presented.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.