• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.51-56
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• 2022

With the development of industrialization, the amount of food and waste is rapidly increasing. Accordingly, the government is aware of the seriousness and is making efforts in various ways to reduce it. As a part of that, the volume-based food system was introduced, and although there were several trials and errors at the beginning of the introduction, it shows a reduction effect of 20 to 30%. These results suggest that the volume-based food system is being established. However, the waste is caused by foreign substances in the process of recycling resources by collecting them from the 1st collection to the 2nd collection process. Therefore, in this study, to solve these problems fundamentally, artificial intelligence is applied to classify foreign substances and improve them. Due to the nature of food waste, there is a limit to obtaining many images, so we compare several models based on CNNs and classify them as abnormal data, that is, CNN-based models are trained on various types of foreign substances, and then models with high accuracy are selected. We intend to prepare improvement measures for maintenance, such as manpower input to protect equipment and classify foreign substances by applying it.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.527-535
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• 2023

To develop experts capable of responding to cyber security incidents, numerous institutions have established cyber training facilities to cultivate security professionals equipped with effective defense strategies. However, these challenges such as limited resources, scenario-based content development, and cost constraints. To address these issues, this paper proposes a virtual infrastructure variation generation framework. It provides customized, diverse IT infrastructure environments for each organization, allowing cyber defense trainers to accumulate a wide range of experiences. By leveraging Infrastructure-as-Code (IaC) containers and employing Word2Vec, a natural language processing model, mutable code elements are extracted and trained, enabling the generation of new code and presenting novel container environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.351-353
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• 2021

In recent years, while the demand for electricity is rapidly increasing, fire accidents due to negligence in management of switchboards. In particular, switchboards for industrial and electrical resource control can cause serious problems. Thus, for the safety management of power switchboard, a secondary response is conducted to control firing when a specific condition value is satisfied, but in this case, it is highly likely that a considerable amount of time has elapsed after firing. In this paper, we propose a method to acquire big data for the development of a switchboard temperature and power control system that can actively respond to the current situation by monitoring and learning the temperature of the switchboard's busbar connection in real time. Specifically, a method for periodically acquiring and managing data such as temperature and power from various scattered sensors is proposed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.203-228
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• 2007

This study was conducted to explore pending issues as an obstacle factor in the library growth and progress through measurement of Korean and Chinese College undergraduates' perception on the library, and suggest its countermeasure to that the study result showed that their perception to the library's social and cultural function was low, so the library's cultural events need to be consolidated to enhance perception, and the Korean student's study zeal was lower than Chinese, and amny students did not go to the library, but an incentive is needed to escalate the strength of course study or the library availability. Also a countermeasure should be established such as a class link project through continuing specialized librarians' training strengthened, users' group education for the satisfaction enhancement and validity of the information service users.

• 한국노년학
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• v.27 no.2
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• pp.299-322
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• 2007

The purpose of this study is to critically review recent discourse on aging appeared in Korean newspapers. For this purpose, 1,725 articles on 'aging' or 'elderly' appeared on three major Korean newspapers during 1997- 2006 are analyzed. It is shown that there is a recent surge of articles portraying the positive images of aging in Korean newspapers emphasizing the importance of productive, successful aging and active life style of the elderly. This trend is a welcomed change from the negative images of elderly as dependent burden of society. However, it seems that over emphasis on positive aging and 'New Elderly' might have created another stereotype about the elderly and unintentionally marginalize the certain group of the elderly. By focusing on individual responsibility, it also overlooked the constraints imposed by social structure on disadvantaged elderly group, such as women, elderly in low socio-economic strata. Theoretical and policy implications of this trends are discussed.

• Journal of Agricultural Education and Human Resource Development
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• v.49 no.4
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• pp.43-65
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• 2017

The purpose of this study is to identify the Issues of the survey on employment status at the vocational high school. For this, 19 chief teachers of employment department were interviewed with the validity of the concept of employment, the appropriateness of the survey period, the effectiveness of the survey method, and the usefulness of the survey output. The main results of research were as follows. First, in the survey of current employment situation, employment is a low standard to be recognized as an ordinary standard, and the employment counts not linked to DB are likely to be inaccurate. Second, regarding the period of employment, the current February survey is difficult to distinguish between field study and employment, and there is a limit to the study of full employment. Third, the present method has limitations on reliability and work efficiency in the survey method. Fourth, current output is not useful for school use in relation to survey output.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.357-359
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• 2022

The market for eco-friendly food materials by online distribution is rapidly growing due to major environmental pollution such as air, soil, and water quality, and radical changes in living patterns caused by COVID-19. In addition, because of the aging population and the decrease in agricultural-related population due to social structural changes, aquaponics is emerging as a system that can solve problems such as independence of old economic activities, environmental protection, and securing healthy and safe food. This paper aims to design an intelligent plant growth measurement system among intelligent aquaponics production management modules for optimal growth environment derivation and quantitative production prediction by converging various ICT technologies into existing aquaponics systems. In particular, the focus is on designing systems suitable for production sites that do not have high-performance processing resources, and we propose a module configuration plan for production environments and training data and prediction systems.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.635-647
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• 2023

In the pursuit of sustained innovation within industries, the consistent emergence of high-growth potential startups is imperative. Despite the government's implementation of diverse investment-based policies aimed at fostering startup initiation, the inherent probability of post-establishment failure for startups remains substantial. This study examines the impact of internal factors on organizational commitment and corporate performance in startups. It emphasizes the significance of learning and networking orientation for commitment across various organizational aspects. Innovativeness affects emotional and normative commitment but not continuance commitment. Financial attributes and global orientation influence continuance commitment, while affective and continuance commitment significantly impact startup performance. Normative cohesion, however, does not significantly affect performance. These findings offer insights for optimizing human resource utilization in startups, benefiting both companies and governments in the evolving startup landscape.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.763-774
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• 2023

The water availability in a river is related to the return flow of residential water. However it is still difficult to determine the exact return flow. In this study, the residential water-cycle system is defined as a process consisting of water inflow, water transfer and water outflow. The study area is Hampyeong-gun, Jeollanam-do, and is set as a single inflow to a single outflow through the water-cycle system after classification of complete and incomplete measurement points. The time-series prediction models(ARIMA model and TFM) are established with daily inflow and outflow data for 6 years. Inflow and outflow are predicted by dividing into training and test periods. As a result, both models show the feasibility of short-term prediction by deriving stable residuals and securing statistical significance, implementing the preliminary form of the water-cycle system. As a further study, it is suggested to predict the actual return flow of the target basin and efficient water operation by adding input factors and selecting the optimal model.