• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2603-2608
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• 2015

Mushroom is a high in protein, low calorie food and has dietary fiber, vitamins, iron and minerals such as zinc. It is called that mushroom is one of the biggest concerns for healthy foods. When we make the artificial cultivation of mushroom, one of the greatest influence element is temperature. In this regard, farmers passively measure temperatures in the greenhouse as inaccurate way such as by the naked eyes. In this paper, we constructed a display system in order to improve the efficiency of manual management of temperature based on the influence of temperature on the mushroom. In related to the methods of mushroom cultivation, the recent technology apply the new technology such as sensors and IT convergence services. And then cultivating mushroom is managed effectively. In this paper, we implement an automatic display system for sensing data. By using this function, farmers could effectively manage environment needed to be grown mushroom, and anticipate the improvement of sales by increasing quality of mushrooms as well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2597-2602
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• 2015

With the development of economy and improving of people's living standards, people dietary needs will be achieved from subsistence to high nutrition and from high nutrition to healthy transformation. Mushroom as a kind of highly nutritious, low fat, rich vitamin food has a great interest among the people. This makes the mushroom into a new sunrise industry and it gradually from pure manual cultivation develops toward the fully automatic factory. In the process of mushroom factory production, regulation of environmental factors directly affects the yield and quality of mushroom. In related to the methods of mushroom cultivation, the recent technologies apply the new technology such as sensors and IT convergence services. And then cultivating mushroom is managed effectively. This paper in order to solve the above problems and construct an effective mushroom growth environment using technology such as humidity sensor construct an environment that can automatically adjust the humidity. This environment has important significance to improve the level of automation mushroom production, increase yield per unit area and quality of mushroom, increase economic efficiency of mushroom production, and enhance the competitiveness of mushroom production.

• Korean journal of applied entomology
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• v.60 no.4
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• pp.493-502
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• 2021

We examined American consumers' perceptions and attitudes toward edible insect-based pet food. In this study, 16 Americans in Korea who owned dogs were categorized into two groups, and focus-group discussions were conducted under three conditions. First, we observed the free association perception of edible insect-based pet food, and attitudes were analyzed after providing a newspaper article related to it. Finally, consumer attitude was examined in the context of purchasing. The study found that the participants had high awareness of the eco-friendliness of edible insects and showed a positive attitude toward news articles related to it. However, when it came to purchasing, they considered nutritional and health functional values compared to environmental values. Meanwhile, the rejection of insects was nevertheless the most important negative factor in pet food, as in general food. The results are significant in confirming the possibility of using insect-based pet food by examining the perceptions and attitudes toward the environmental, nutritional, and health functional values of edible insects under three conditions for American consumers.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.337-347
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• 2018

Weather causes much of the risk of agricultural activity. For efficient farming, we need to use weather information. Modern agriculture has been developed to create high added value through convergence with state-of-the-art Information and Communication Technology (ICT). This study deals with the quality control algorithms of weather monitoring equipment through Ubiquitous Sensor Network (USN) observational equipment for efficient cultivation of cabbage. Accurate weather observations are important. To achieve this goal, the Korea Meteorological Administration, for example, developed various quality control algorithms to determine regularity of the observation. The research data of this study were obtained from five USN stations, which were installed in Anbandegi and Gwinemi from 2015 to 2017. Quality control algorithms were developed for flat line check, temporal outliers check, time series consistency check and spatial outliers check. Finally, the quality control algorithms proposed in this study can also identify potential abnormal observations taking into account the temporal and spatial characteristics of weather data. It is expected to be useful for efficient management of highland cabbage production by providing quality-controlled weather data.

• Informatization Policy
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• v.25 no.4
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• pp.3-36
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• 2018

This article discusses the possibilities and limitations of ICT education by reviewing the previous research on its various aspects including educational goals, contents, methods, and evaluation. First, when it comes to its educational goal, the prior studies suggest that ICT education aims to nurture digital citizenship among students and to enable them to participate in different sectors of our society. ICT education characterizes the core capacities of its future learners as 'lifelong learners,' 'information producers/consumers,' and 'local/global citizens.' Second, in regard to the educational content of ICT education, researchers investigate SW education importantly: They develop the educational programs and examine the effectiveness of those programs. However, to ensure the relevancy of the educational contents to the future society, institutional support is imperative including facilitating educators' capacities and synchronizing ICT education with subject education. Third, as the educational methods, various ICTs such as flipped learning and augmented reality (AR) are being applied to actual classroom teaching. Research on the educational methods, which is the most vibrant area in the ICT education scholarship, is expected to improve the previous educational methods and to lead the qualitative development of ICT education. Fourth, the previous discussion on the educational evaluation focuses on computer-based evaluations. Educational evaluation using ICT will enable educators to assess the characteristics and achievement of an individual learner accurately and to lead them to apply a teaching-learning process effectively, which will ultimately enhance the effectiveness of educational evaluation. Along with the overall review on the possibilities of ICT education, this article discusses the limitations of the current ICT education and its implications for educational inequalities.

• Agribusiness and Information Management
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• v.13 no.1
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• pp.26-40
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• 2021

During the pandemic status of COVID-19 since 2019 December, demands and attention on various convergence services with non-contact technologies and social adoption are increasing. Along with these increased demands and attention, the digital divide issues should be concerned to understand the informatization degrees of rural area residences, the elderly, the disabled, and the low-income. Furthermore, rural area residences may be the elderly, the disabled, and the low-income also. It may mean that the rural area should be considered as in noticeable status of the digital divide. This study focuses on the policy alternatives to reduce the digital divide in rural areas with a literature review methodology and on the factors on informatization issues in rural areas. For the aims, this study analyzes the EU cases of informatization in rural areas to find out the advantages and disadvantages of the suggested policies. As the analysis result, it is clear that the EU countries try to enhance the economic and growth powers rather to reduce the digital divide gaps. Also, it can be considered that the EU countries focus on supporting the rural area to adopt the non-contact information services newly rather on maintaining the IT education services and the infrastructures in off-line environments.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.473-481
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• 2020

Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.244-255
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• 2022

This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.